diff --git a/.gitignore b/.gitignore
index c727996..8840982 100644
--- a/.gitignore
+++ b/.gitignore
@@ -165,4 +165,7 @@ dump/
 .vscode/
 **generated_images/
 .ruff_cache/
-**.jsonl
\ No newline at end of file
+**.jsonl
+test.py
+inference_dataset/
+uv.lock
diff --git a/README.md b/README.md
index 6302446..447cdfc 100644
--- a/README.md
+++ b/README.md
@@ -41,8 +41,9 @@ import wandb
 import weave
 
 
-from hemm.eval_pipelines import BaseDiffusionModel, EvaluationPipeline
+from hemm.eval_pipelines import EvaluationPipeline
 from hemm.metrics.prompt_alignment import CLIPImageQualityScoreMetric, CLIPScoreMetric
+from hemm.models import BaseDiffusionModel
 
 
 # Initialize Weave and WandB
diff --git a/docs/models/diffusion_model.md b/docs/models/diffusion_model.md
new file mode 100644
index 0000000..7b242b4
--- /dev/null
+++ b/docs/models/diffusion_model.md
@@ -0,0 +1,3 @@
+# Diffusion Models
+
+::: hemm.models.diffusion_model
\ No newline at end of file
diff --git a/docs/models/falai_model.md b/docs/models/falai_model.md
new file mode 100644
index 0000000..f135dba
--- /dev/null
+++ b/docs/models/falai_model.md
@@ -0,0 +1,3 @@
+# FalAI Models
+
+::: hemm.models.falai_model
\ No newline at end of file
diff --git a/docs/models/stability_model.md b/docs/models/stability_model.md
new file mode 100644
index 0000000..f525857
--- /dev/null
+++ b/docs/models/stability_model.md
@@ -0,0 +1,3 @@
+# StabilityAI Model
+
+::: hemm.models.stability_model
\ No newline at end of file
diff --git a/examples/2d_spatial_eval/evaluate_spatial_relationship_detr.py b/examples/2d_spatial_eval/evaluate_spatial_relationship_detr.py
index 25a1190..d718e83 100644
--- a/examples/2d_spatial_eval/evaluate_spatial_relationship_detr.py
+++ b/examples/2d_spatial_eval/evaluate_spatial_relationship_detr.py
@@ -1,12 +1,13 @@
 from typing import Optional, Tuple
 
 import fire
-import wandb
 import weave
 
-from hemm.eval_pipelines import BaseDiffusionModel, EvaluationPipeline
+import wandb
+from hemm.eval_pipelines import EvaluationPipeline
 from hemm.metrics.spatial_relationship import SpatialRelationshipMetric2D
 from hemm.metrics.spatial_relationship.judges import DETRSpatialRelationShipJudge
+from hemm.models import BaseDiffusionModel
 
 
 def main(
diff --git a/examples/2d_spatial_eval/evaluate_spatial_relationship_rt_detr.py b/examples/2d_spatial_eval/evaluate_spatial_relationship_rt_detr.py
index 0de024d..d5a2c3e 100644
--- a/examples/2d_spatial_eval/evaluate_spatial_relationship_rt_detr.py
+++ b/examples/2d_spatial_eval/evaluate_spatial_relationship_rt_detr.py
@@ -1,12 +1,13 @@
 from typing import Optional, Tuple
 
 import fire
-import wandb
 import weave
 
-from hemm.eval_pipelines import BaseDiffusionModel, EvaluationPipeline
+import wandb
+from hemm.eval_pipelines import EvaluationPipeline
 from hemm.metrics.spatial_relationship import SpatialRelationshipMetric2D
 from hemm.metrics.spatial_relationship.judges import RTDETRSpatialRelationShipJudge
+from hemm.models import BaseDiffusionModel
 
 
 def main(
diff --git a/examples/disentangled_vqa/evaluate_disentangled_vqa.py b/examples/disentangled_vqa/evaluate_disentangled_vqa.py
index 160d305..afef6d7 100644
--- a/examples/disentangled_vqa/evaluate_disentangled_vqa.py
+++ b/examples/disentangled_vqa/evaluate_disentangled_vqa.py
@@ -1,12 +1,13 @@
 from typing import Optional, Tuple
 
 import fire
-import wandb
 import weave
 
-from hemm.eval_pipelines import BaseDiffusionModel, EvaluationPipeline
+import wandb
+from hemm.eval_pipelines import EvaluationPipeline
 from hemm.metrics.vqa import DisentangledVQAMetric
 from hemm.metrics.vqa.judges import BlipVQAJudge
+from hemm.models import BaseDiffusionModel
 
 
 def main(
diff --git a/examples/evaluate_weave_image_quality.py b/examples/evaluate_weave_image_quality.py
index f3fa628..f1de969 100644
--- a/examples/evaluate_weave_image_quality.py
+++ b/examples/evaluate_weave_image_quality.py
@@ -1,9 +1,10 @@
 import fire
-import wandb
 import weave
 
-from hemm.eval_pipelines import BaseDiffusionModel, EvaluationPipeline
+import wandb
+from hemm.eval_pipelines import EvaluationPipeline
 from hemm.metrics.image_quality import LPIPSMetric, PSNRMetric, SSIMMetric
+from hemm.models import BaseDiffusionModel
 
 
 def main(
diff --git a/examples/evaluate_weave_prompt_alignment.py b/examples/evaluate_weave_prompt_alignment.py
index 469cd9d..ddacaaf 100644
--- a/examples/evaluate_weave_prompt_alignment.py
+++ b/examples/evaluate_weave_prompt_alignment.py
@@ -1,9 +1,10 @@
 import fire
-import wandb
 import weave
 
-from hemm.eval_pipelines import BaseDiffusionModel, EvaluationPipeline
+import wandb
+from hemm.eval_pipelines import EvaluationPipeline
 from hemm.metrics.prompt_alignment import CLIPImageQualityScoreMetric, CLIPScoreMetric
+from hemm.models import BaseDiffusionModel
 
 
 def main(
diff --git a/examples/multimodal_llm_eval/evaluate_mllm_metric_action.py b/examples/multimodal_llm_eval/evaluate_mllm_metric_action.py
new file mode 100644
index 0000000..738387b
--- /dev/null
+++ b/examples/multimodal_llm_eval/evaluate_mllm_metric_action.py
@@ -0,0 +1,59 @@
+from typing import Optional
+
+import fire
+import weave
+
+import wandb
+from hemm.eval_pipelines import EvaluationPipeline
+from hemm.metrics.vqa import MultiModalLLMEvaluationMetric
+from hemm.metrics.vqa.judges.mmllm_judges import OpenAIJudge, PromptCategory
+from hemm.models import BaseDiffusionModel
+
+
+def main(
+    project="mllm-eval",
+    entity="hemm-eval",
+    dataset_ref: Optional[str] = "attribute_binding_dataset:v1",
+    dataset_limit: Optional[int] = None,
+    diffusion_model_address: str = "stabilityai/stable-diffusion-2-1",
+    diffusion_model_enable_cpu_offfload: bool = False,
+    openai_judge_model: str = "gpt-4o",
+    image_height: int = 1024,
+    image_width: int = 1024,
+    num_inference_steps: int = 50,
+    mock_inference_dataset_address: Optional[str] = None,
+    save_inference_dataset_name: Optional[str] = None,
+):
+    wandb.init(project=project, entity=entity, job_type="evaluation")
+    weave.init(project_name=f"{entity}/{project}")
+
+    dataset = weave.ref(dataset_ref).get()
+    dataset = dataset.rows[:dataset_limit] if dataset_limit else dataset
+
+    diffusion_model = BaseDiffusionModel(
+        diffusion_model_name_or_path=diffusion_model_address,
+        enable_cpu_offfload=diffusion_model_enable_cpu_offfload,
+        image_height=image_height,
+        image_width=image_width,
+        num_inference_steps=num_inference_steps,
+    )
+    diffusion_model._pipeline.set_progress_bar_config(disable=True)
+    evaluation_pipeline = EvaluationPipeline(
+        model=diffusion_model,
+        mock_inference_dataset_address=mock_inference_dataset_address,
+        save_inference_dataset_name=save_inference_dataset_name,
+    )
+
+    judge = OpenAIJudge(
+        prompt_property=PromptCategory.action, openai_model=openai_judge_model
+    )
+    metric = MultiModalLLMEvaluationMetric(judge=judge)
+    evaluation_pipeline.add_metric(metric)
+
+    evaluation_pipeline(dataset=dataset)
+    wandb.finish()
+    evaluation_pipeline.cleanup()
+
+
+if __name__ == "__main__":
+    fire.Fire(main)
diff --git a/examples/multimodal_llm_eval/evaluate_mllm_metric_complex.py b/examples/multimodal_llm_eval/evaluate_mllm_metric_complex.py
index bf37ce2..738387b 100644
--- a/examples/multimodal_llm_eval/evaluate_mllm_metric_complex.py
+++ b/examples/multimodal_llm_eval/evaluate_mllm_metric_complex.py
@@ -1,12 +1,13 @@
 from typing import Optional
 
 import fire
-import wandb
 import weave
 
-from hemm.eval_pipelines import BaseDiffusionModel, EvaluationPipeline
+import wandb
+from hemm.eval_pipelines import EvaluationPipeline
 from hemm.metrics.vqa import MultiModalLLMEvaluationMetric
 from hemm.metrics.vqa.judges.mmllm_judges import OpenAIJudge, PromptCategory
+from hemm.models import BaseDiffusionModel
 
 
 def main(
@@ -16,9 +17,12 @@ def main(
     dataset_limit: Optional[int] = None,
     diffusion_model_address: str = "stabilityai/stable-diffusion-2-1",
     diffusion_model_enable_cpu_offfload: bool = False,
+    openai_judge_model: str = "gpt-4o",
     image_height: int = 1024,
     image_width: int = 1024,
     num_inference_steps: int = 50,
+    mock_inference_dataset_address: Optional[str] = None,
+    save_inference_dataset_name: Optional[str] = None,
 ):
     wandb.init(project=project, entity=entity, job_type="evaluation")
     weave.init(project_name=f"{entity}/{project}")
@@ -34,13 +38,21 @@ def main(
         num_inference_steps=num_inference_steps,
     )
     diffusion_model._pipeline.set_progress_bar_config(disable=True)
-    evaluation_pipeline = EvaluationPipeline(model=diffusion_model)
+    evaluation_pipeline = EvaluationPipeline(
+        model=diffusion_model,
+        mock_inference_dataset_address=mock_inference_dataset_address,
+        save_inference_dataset_name=save_inference_dataset_name,
+    )
 
-    judge = OpenAIJudge(prompt_property=PromptCategory.action)
+    judge = OpenAIJudge(
+        prompt_property=PromptCategory.action, openai_model=openai_judge_model
+    )
     metric = MultiModalLLMEvaluationMetric(judge=judge)
     evaluation_pipeline.add_metric(metric)
 
     evaluation_pipeline(dataset=dataset)
+    wandb.finish()
+    evaluation_pipeline.cleanup()
 
 
 if __name__ == "__main__":
diff --git a/hemm/eval_pipelines/__init__.py b/hemm/eval_pipelines/__init__.py
index e95cb96..dea3c26 100644
--- a/hemm/eval_pipelines/__init__.py
+++ b/hemm/eval_pipelines/__init__.py
@@ -1,4 +1,3 @@
 from .eval_pipeline import EvaluationPipeline
-from .model import BaseDiffusionModel
 
-__all__ = ["BaseDiffusionModel", "EvaluationPipeline"]
+__all__ = ["EvaluationPipeline"]
diff --git a/hemm/eval_pipelines/eval_pipeline.py b/hemm/eval_pipelines/eval_pipeline.py
index 15d46c8..f241a4e 100644
--- a/hemm/eval_pipelines/eval_pipeline.py
+++ b/hemm/eval_pipelines/eval_pipeline.py
@@ -1,12 +1,18 @@
 import asyncio
+import os
+import shutil
 from abc import ABC
-from typing import Dict, List, Union
+from typing import Dict, List, Optional, Union
 
-import wandb
 import weave
+from PIL import Image
+
+import wandb
 
 from ..metrics.base import BaseMetric
-from .model import BaseDiffusionModel
+from ..models import BaseDiffusionModel, FalAIModel, StabilityAPIModel
+
+MODEL_TYPE = Union[BaseDiffusionModel, FalAIModel, StabilityAPIModel]
 
 
 class EvaluationPipeline(ABC):
@@ -15,16 +21,43 @@ class EvaluationPipeline(ABC):
     Args:
         model (BaseDiffusionModel): The model to evaluate.
         seed (int): Seed value for the random number generator.
+        mock_inference_dataset_address (Optional[str]): A wandb dataset artifact address which if
+            provided will mock inference results. This prevents the need for redundant generations
+            when switching metrics/judges with the same evaluation datset(s).
+        save_inference_dataset_name (Optional[str]): A weave dataset name which if provided will
+            save inference results as a separate weave dataset.
     """
 
-    def __init__(self, model: BaseDiffusionModel, seed: int = 42) -> None:
+    def __init__(
+        self,
+        model: MODEL_TYPE,
+        seed: int = 42,
+        mock_inference_dataset_address: Optional[str] = None,
+        save_inference_dataset_name: Optional[str] = None,
+    ) -> None:
         super().__init__()
         self.model = model
 
         self.image_size = (self.model.image_height, self.model.image_width)
         self.seed = seed
-
-        self.inference_counter = 1
+        self.mock_inference_dataset_address = mock_inference_dataset_address
+        if mock_inference_dataset_address:
+            self.save_inference_dataset_name = None
+            artifact = wandb.use_artifact(
+                self.mock_inference_dataset_address, type="dataset"
+            )
+            self.mock_inference_dataset_dir = artifact.download()
+
+        else:
+            self.save_inference_dataset_name = save_inference_dataset_name
+
+        if self.save_inference_dataset_name:
+            os.makedirs(
+                os.path.join("inference_dataset", self.save_inference_dataset_name),
+                exist_ok=True,
+            )
+
+        self.inference_counter = 0
         self.table_columns = ["model", "prompt", "generated_image"]
         self.table_rows: List = []
         self.evaluation_table: wandb.Table = None
@@ -63,13 +96,29 @@ def infer(self, prompt: str) -> Dict[str, str]:
             Dict[str, str]: Dictionary containing base64 encoded image to be logged as
                 a Weave object.
         """
-        if self.inference_counter == 1:
+        if self.inference_counter == 0:
             self.evaluation_table = wandb.Table(columns=self.table_columns)
-        self.inference_counter += 1
-        output = self.model.predict(prompt, seed=self.seed)
+        if self.mock_inference_dataset_address:
+            image = Image.open(
+                os.path.join(
+                    self.mock_inference_dataset_dir, f"{self.inference_counter}.png"
+                )
+            )
+            output = {"image": image}
+        else:
+            output = self.model.predict(prompt, seed=self.seed)
         self.table_rows.append(
             [self.model.diffusion_model_name_or_path, prompt, output["image"]]
         )
+        if self.save_inference_dataset_name:
+            output["image"].save(
+                os.path.join(
+                    "inference_dataset",
+                    self.save_inference_dataset_name,
+                    f"{self.inference_counter}.png",
+                )
+            )
+        self.inference_counter += 1
         return output
 
     @weave.op()
@@ -104,19 +153,40 @@ def log_summary(self, summary: Dict[str, float]) -> None:
             }
         )
 
-    def __call__(self, dataset: Union[List[Dict], str]) -> Dict[str, float]:
+    def save_inference_results(self):
+        artifact = wandb.Artifact(name=self.save_inference_dataset_name, type="dataset")
+        artifact.add_dir(
+            os.path.join("inference_dataset", self.save_inference_dataset_name)
+        )
+        artifact.save()
+
+    def cleanup(self):
+        """Cleanup the inference dataset directory. Should be called after the evaluation is complete
+        and `wandb.finish()` is called."""
+        if os.path.exists("inference_dataset"):
+            shutil.rmtree("inference_dataset")
+
+    def __call__(
+        self, dataset: Union[List[Dict], str], async_infer: bool = False
+    ) -> Dict[str, float]:
         """Evaluate the Stable Diffusion model on the given dataset.
 
         Args:
             dataset (Union[List[Dict], str]): Dataset to evaluate the model on. If a string is
                 passed, it is assumed to be a Weave dataset reference.
+            async_infer (bool, optional): Whether to use async inference. Defaults to False.
         """
         dataset = weave.ref(dataset).get() if isinstance(dataset, str) else dataset
         evaluation = weave.Evaluation(
             dataset=dataset,
-            scorers=[metric_fn.evaluate_async for metric_fn in self.metric_functions],
+            scorers=[
+                metric_fn.evaluate_async if async_infer else metric_fn.evaluate
+                for metric_fn in self.metric_functions
+            ],
         )
         self.model.configs.update(self.evaluation_configs)
         summary = asyncio.run(evaluation.evaluate(self.infer_async))
         self.log_summary(summary)
+        if self.save_inference_dataset_name:
+            self.save_inference_results()
         return summary
diff --git a/hemm/metrics/spatial_relationship/analyze_prompt.py b/hemm/metrics/spatial_relationship/analyze_prompt.py
index 5b78942..2779571 100644
--- a/hemm/metrics/spatial_relationship/analyze_prompt.py
+++ b/hemm/metrics/spatial_relationship/analyze_prompt.py
@@ -4,11 +4,12 @@
 from typing import Dict, List, Optional
 
 import jsonlines
-import wandb
 import weave
 from openai import OpenAI
 from weave import Dataset, Evaluation, Model
 
+import wandb
+
 
 def chunk_all_prompts(prompt_list: List[str], chunk_size: int) -> List[str]:
     """Chunk all prompts into smaller chunks of size `chunk_size`.
diff --git a/hemm/metrics/spatial_relationship/spatial_relationship_2d.py b/hemm/metrics/spatial_relationship/spatial_relationship_2d.py
index c2e89ab..dae173a 100644
--- a/hemm/metrics/spatial_relationship/spatial_relationship_2d.py
+++ b/hemm/metrics/spatial_relationship/spatial_relationship_2d.py
@@ -1,9 +1,10 @@
 from typing import Any, Dict, List, Optional, Union
 
-import wandb
 import weave
 from PIL import Image
 
+import wandb
+
 from ..base import BaseMetric
 from .judges import DETRSpatialRelationShipJudge
 from .judges.commons import BoundingBox
diff --git a/hemm/metrics/vqa/dataset_generator/attribute_binding.py b/hemm/metrics/vqa/dataset_generator/attribute_binding.py
index 2fa0be3..aa379fe 100644
--- a/hemm/metrics/vqa/dataset_generator/attribute_binding.py
+++ b/hemm/metrics/vqa/dataset_generator/attribute_binding.py
@@ -3,11 +3,12 @@
 from typing import Dict, List, Optional, Union
 
 import jsonlines
-import wandb
 import weave
 from openai import OpenAI
 from pydantic import BaseModel
 
+import wandb
+
 from ....utils import autogenerate_seed, str_to_json
 
 
diff --git a/hemm/metrics/vqa/judges/mmllm_judges/openai_judge.py b/hemm/metrics/vqa/judges/mmllm_judges/openai_judge.py
index c340058..b3fbd75 100644
--- a/hemm/metrics/vqa/judges/mmllm_judges/openai_judge.py
+++ b/hemm/metrics/vqa/judges/mmllm_judges/openai_judge.py
@@ -2,20 +2,14 @@
 import subprocess
 from typing import List
 
-import instructor
 import spacy
 import weave
 from openai import OpenAI
 from PIL import Image
 from pydantic import BaseModel
 
-from .commons import (
-    PromptCategory,
-    TaggedPromptParts,
-    JudgeMent,
-    JudgeQuestion,
-)
 from .....utils import base64_encode_image
+from .commons import JudgeMent, JudgeQuestion, PromptCategory, TaggedPromptParts
 
 
 class OpenAIJudgeMent(BaseModel):
@@ -48,14 +42,13 @@ class OpenAIJudge(weave.Model):
     seed: int
     _nlp_pipeline: spacy.Language = None
     _openai_client: OpenAI = None
-    _instructor_openai_client: instructor.Instructor = None
     _total_score: int = 4
 
     def __init__(
         self,
         prompt_pipeline: str = "en_core_web_sm",
         prompt_property: PromptCategory = PromptCategory.color,
-        openai_model: str = "gpt-4-turbo",
+        openai_model: str = "gpt-4o-2024-08-06",
         max_retries: int = 5,
         seed: int = 42,
     ):
@@ -69,9 +62,6 @@ def __init__(
         subprocess.run(["spacy", "download", "en_core_web_sm"])
         self._nlp_pipeline = spacy.load(self.prompt_pipeline)
         self._openai_client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
-        self._instructor_openai_client = instructor.from_openai(
-            OpenAI(api_key=os.environ["OPENAI_API_KEY"])
-        )
 
     @weave.op()
     def extract_prompt_parts(self, prompt: str) -> List[TaggedPromptParts]:
@@ -318,27 +308,30 @@ def execute_chain_of_thought(
 
 Provide your analysis and explanation to justify the score.
         """
-        judgement_response = self._instructor_openai_client.chat.completions.create(
-            model=self.openai_model,
-            response_model=JudgeMent,
-            max_retries=self.max_retries,
-            seed=self.seed,
-            messages=[
-                {
-                    "role": "system",
-                    "content": question.judgement_question_system_prompt,
-                },
-                {
-                    "role": "user",
-                    "content": [
-                        {"type": "text", "text": question.judgement_question},
-                        {
-                            "type": "image_url",
-                            "image_url": {"url": base64_encode_image(image)},
-                        },
-                    ],
-                },
-            ],
+        judgement_response = (
+            self._openai_client.beta.chat.completions.parse(
+                model=self.openai_model,
+                response_format=JudgeMent,
+                seed=self.seed,
+                messages=[
+                    {
+                        "role": "system",
+                        "content": question.judgement_question_system_prompt,
+                    },
+                    {
+                        "role": "user",
+                        "content": [
+                            {"type": "text", "text": question.judgement_question},
+                            {
+                                "type": "image_url",
+                                "image_url": {"url": base64_encode_image(image)},
+                            },
+                        ],
+                    },
+                ],
+            )
+            .choices[0]
+            .message.parsed
         )
         return judgement_response
 
diff --git a/hemm/models/__init__.py b/hemm/models/__init__.py
new file mode 100644
index 0000000..883d860
--- /dev/null
+++ b/hemm/models/__init__.py
@@ -0,0 +1,5 @@
+from .diffusion_model import BaseDiffusionModel
+from .falai_model import FalAIModel
+from .stability_model import StabilityAPIModel
+
+__all__ = ["BaseDiffusionModel", "FalAIModel", "StabilityAPIModel"]
diff --git a/hemm/eval_pipelines/model.py b/hemm/models/diffusion_model.py
similarity index 90%
rename from hemm/eval_pipelines/model.py
rename to hemm/models/diffusion_model.py
index c0d3a3a..2cfe0ba 100644
--- a/hemm/eval_pipelines/model.py
+++ b/hemm/models/diffusion_model.py
@@ -6,14 +6,18 @@
 
 
 class BaseDiffusionModel(weave.Model):
-    """Base `weave.Model` wrapping `diffusers.DiffusionPipeline`.
+    """`weave.Model` wrapping `diffusers.DiffusionPipeline`.
 
     Args:
         diffusion_model_name_or_path (str): The name or path of the diffusion model.
         enable_cpu_offfload (bool): Enable CPU offload for the diffusion model.
         image_height (int): The height of the generated image.
         image_width (int): The width of the generated image.
+        num_inference_steps (int): The number of inference steps.
         disable_safety_checker (bool): Disable safety checker for the diffusion model.
+        configs (Dict[str, Any]): Additional configs.
+        pipeline_configs (Dict[str, Any]): Diffusion pipeline configs.
+        inference_kwargs (Dict[str, Any]): Inference kwargs.
     """
 
     diffusion_model_name_or_path: str
diff --git a/hemm/models/falai_model.py b/hemm/models/falai_model.py
new file mode 100644
index 0000000..e02efe9
--- /dev/null
+++ b/hemm/models/falai_model.py
@@ -0,0 +1,34 @@
+from typing import Any, Dict
+
+import fal_client
+import weave
+from diffusers.utils.loading_utils import load_image
+from PIL import Image
+
+from ..utils import custom_weave_wrapper
+
+
+class FalAIModel(weave.Model):
+    """`weave.Model` wrapping [FalAI](https://fal.ai/) calls.
+
+    Args:
+        model_name (str): FalAI model name.
+        inference_kwargs (Dict[str, Any]): Inference kwargs.
+    """
+
+    model_name: str
+    inference_kwargs: Dict[str, Any] = {}
+
+    @weave.op()
+    def generate_image(self, prompt: str, seed: int) -> Image.Image:
+        result = custom_weave_wrapper(name="fal_client.submit.get")(
+            fal_client.submit(
+                self.model_name,
+                arguments={"prompt": prompt, "seed": seed, **self.inference_kwargs},
+            ).get
+        )()
+        return load_image(result["images"][0]["url"])
+
+    @weave.op()
+    def predict(self, prompt: str, seed: int) -> Image.Image:
+        return {"image": self.generate_image(prompt=prompt, seed=seed)}
diff --git a/hemm/models/stability_model.py b/hemm/models/stability_model.py
new file mode 100644
index 0000000..cdb838c
--- /dev/null
+++ b/hemm/models/stability_model.py
@@ -0,0 +1,77 @@
+import io
+import os
+from typing import Any, Dict
+
+import requests
+import weave
+from PIL import Image
+
+STABILITY_MODEL_HOST = {
+    "sd3-large": "https://api.stability.ai/v2beta/stable-image/generate/sd3",
+    "sd3-large-turbo": "https://api.stability.ai/v2beta/stable-image/generate/sd3",
+}
+
+
+class StabilityAPIModel(weave.Model):
+    """`weave.Model` wrapping Stability API calls.
+
+    Args:
+        model_name (str): Stability model name.
+        aspect_ratio (str): Aspect ratio of the generated image.
+        creativity (float): Creativity of the generated image.
+    """
+
+    model_name: str
+    aspect_ratio: str = "1:1"
+    creativity: float = 0.35
+    configs: Dict[str, Any] = {}
+
+    def __init__(
+        self,
+        model_name: str,
+        aspect_ratio: str = "1:1",
+        creativity: float = 0.35,
+    ) -> None:
+        assert aspect_ratio in [
+            "1:1",
+            "16:9",
+            "21:9",
+            "2:3",
+            "3:2",
+            "4:5",
+            "5:4",
+            "9:16",
+            "9:21",
+        ], "Invalid aspect ratio"
+        super().__init__(
+            model_name=model_name, aspect_ratio=aspect_ratio, creativity=creativity
+        )
+
+    @weave.op()
+    def send_generation_request(self, prompt: str, seed: int):
+        api_key = os.environ["STABILITY_KEY"]
+        headers = {"Accept": "image/*", "Authorization": f"Bearer {api_key}"}
+        response = requests.post(
+            STABILITY_MODEL_HOST[self.model_name],
+            headers=headers,
+            files={"none": ""},
+            data={
+                "prompt": prompt,
+                "negative_prompt": "",
+                "aspect_ratio": self.aspect_ratio,
+                "seed": seed,
+                "output_format": "png",
+                "model": self.model_name,
+                "mode": "text-to-image",
+                "creativity": self.creativity,
+            },
+        )
+        if not response.ok:
+            raise Exception(f"HTTP {response.status_code}: {response.text}")
+        return response
+
+    @weave.op()
+    def predict(self, prompt: str, seed: int) -> Image.Image:
+        response = self.send_generation_request(prompt=prompt, seed=seed)
+        image = Image.open(io.BytesIO(response.content))
+        return {"image": image}
diff --git a/hemm/tests/test_2d_spatial_relationship_eval.py b/hemm/tests/test_2d_spatial_relationship_eval.py
index 4e251ab..4cd3f2d 100644
--- a/hemm/tests/test_2d_spatial_relationship_eval.py
+++ b/hemm/tests/test_2d_spatial_relationship_eval.py
@@ -1,8 +1,8 @@
 import unittest
 
-import wandb
 import weave
 
+import wandb
 from hemm.eval_pipelines import BaseDiffusionModel, EvaluationPipeline
 from hemm.metrics.spatial_relationship import SpatialRelationshipMetric2D
 from hemm.metrics.spatial_relationship.judges import (
diff --git a/hemm/tests/test_disentangled_vqa.py b/hemm/tests/test_disentangled_vqa.py
index 8ff761c..669355f 100644
--- a/hemm/tests/test_disentangled_vqa.py
+++ b/hemm/tests/test_disentangled_vqa.py
@@ -1,8 +1,8 @@
 import unittest
 
-import wandb
 import weave
 
+import wandb
 from hemm.eval_pipelines import BaseDiffusionModel, EvaluationPipeline
 from hemm.metrics.vqa import DisentangledVQAMetric
 from hemm.metrics.vqa.judges import BlipVQAJudge
diff --git a/hemm/tests/test_image_quality_eval.py b/hemm/tests/test_image_quality_eval.py
index 8705969..f254ee9 100644
--- a/hemm/tests/test_image_quality_eval.py
+++ b/hemm/tests/test_image_quality_eval.py
@@ -1,8 +1,8 @@
 import unittest
 
-import wandb
 import weave
 
+import wandb
 from hemm.eval_pipelines import BaseDiffusionModel, EvaluationPipeline
 from hemm.metrics.image_quality import LPIPSMetric, PSNRMetric, SSIMMetric
 
diff --git a/hemm/tests/test_mllm_eval.py b/hemm/tests/test_mllm_eval.py
index 90f2fb0..415ed3b 100644
--- a/hemm/tests/test_mllm_eval.py
+++ b/hemm/tests/test_mllm_eval.py
@@ -1,8 +1,8 @@
 import unittest
 
-import wandb
 import weave
 
+import wandb
 from hemm.eval_pipelines import BaseDiffusionModel, EvaluationPipeline
 from hemm.metrics.vqa import MultiModalLLMEvaluationMetric
 from hemm.metrics.vqa.judges.mmllm_judges import OpenAIJudge, PromptCategory
diff --git a/hemm/tests/test_prompt_alignment_eval.py b/hemm/tests/test_prompt_alignment_eval.py
index 9a18e19..a876455 100644
--- a/hemm/tests/test_prompt_alignment_eval.py
+++ b/hemm/tests/test_prompt_alignment_eval.py
@@ -1,8 +1,8 @@
 import unittest
 
-import wandb
 import weave
 
+import wandb
 from hemm.eval_pipelines import BaseDiffusionModel, EvaluationPipeline
 from hemm.metrics.prompt_alignment import CLIPImageQualityScoreMetric, CLIPScoreMetric
 
diff --git a/hemm/tests/test_utils.py b/hemm/tests/test_utils.py
index 4d03aa7..583c3ae 100644
--- a/hemm/tests/test_utils.py
+++ b/hemm/tests/test_utils.py
@@ -1,6 +1,7 @@
 import unittest
 
 import weave
+
 from hemm.utils import publish_dataset_to_weave
 
 
diff --git a/hemm/utils.py b/hemm/utils.py
index 447150c..e9dc091 100644
--- a/hemm/utils.py
+++ b/hemm/utils.py
@@ -155,3 +155,12 @@ def autogenerate_seed(set_to_max: bool = False) -> int:
     seed = -seed if seed < 0 else seed
     seed = seed % max_seed
     return seed
+
+
+def custom_weave_wrapper(name: str) -> Callable[[Callable], Callable]:
+    def wrapper(fn: Callable) -> Callable:
+        op = weave.op()(fn)
+        op.name = name  # type: ignore
+        return op
+
+    return wrapper
diff --git a/mkdocs.yml b/mkdocs.yml
index b5fd04a..c66a0e9 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -3,6 +3,17 @@ site_name: Hemm
 
 theme:
   name: material
+  palette: 
+    # Palette toggle for light mode
+    - scheme: default
+      toggle:
+        icon: material/brightness-7 
+        name: Switch to dark mode
+    # Palette toggle for dark mode
+    - scheme: slate
+      toggle:
+        icon: material/brightness-4
+        name: Switch to light mode
   logo: assets/wandb_logo.svg
   favicon: assets/wandb_logo.svg
   features:
@@ -47,6 +58,10 @@ extra_javascript:
 nav:
   - Home: 'index.md'
   - Evaluation-Pipelines: 'eval_pipelines.md'
+  - Models:
+    - Diffusion-Models: 'models/diffusion_model.md'
+    - FalAI-Models: 'models/falai_model.md'
+    - StabilityAI-Models: 'models/stability_model.md'
   - Metrics:
     - Image-Quality-Metrics: 'metrics/image_quality.md'
     - Prompt-Image-Alignment: 'metrics/prompt_image_alignment.md'
diff --git a/poetry.lock b/poetry.lock
deleted file mode 100644
index e33bbe5..0000000
--- a/poetry.lock
+++ /dev/null
@@ -1,7044 +0,0 @@
-# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
-
-[[package]]
-name = "accelerate"
-version = "0.30.1"
-description = "Accelerate"
-optional = false
-python-versions = ">=3.8.0"
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-    {file = "accelerate-0.30.1.tar.gz", hash = "sha256:96779c618889646b86dc928c9e55e86e50a7ccab59e1692e22096481977ae682"},
-]
-
-[package.dependencies]
-huggingface-hub = "*"
-numpy = ">=1.17"
-packaging = ">=20.0"
-psutil = "*"
-pyyaml = "*"
-safetensors = ">=0.3.1"
-torch = ">=1.10.0"
-
-[package.extras]
-deepspeed = ["deepspeed (<=0.14.0)"]
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-quality = ["black (>=23.1,<24.0)", "hf-doc-builder (>=0.3.0)", "ruff (>=0.2.1,<0.3.0)"]
-rich = ["rich"]
-sagemaker = ["sagemaker"]
-test-dev = ["bitsandbytes", "datasets", "diffusers", "evaluate", "scikit-learn", "scipy", "timm", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
-test-prod = ["parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist"]
-test-trackers = ["comet-ml", "dvclive", "tensorboard", "wandb"]
-testing = ["bitsandbytes", "datasets", "diffusers", "evaluate", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist", "scikit-learn", "scipy", "timm", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
-
-[[package]]
-name = "aiofiles"
-version = "23.2.1"
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-python-versions = ">=3.7"
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-]
-
-[package.dependencies]
-idna = ">=2.0"
-multidict = ">=4.0"
-
-[[package]]
-name = "zipp"
-version = "3.18.1"
-description = "Backport of pathlib-compatible object wrapper for zip files"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "zipp-3.18.1-py3-none-any.whl", hash = "sha256:206f5a15f2af3dbaee80769fb7dc6f249695e940acca08dfb2a4769fe61e538b"},
-    {file = "zipp-3.18.1.tar.gz", hash = "sha256:2884ed22e7d8961de1c9a05142eb69a247f120291bc0206a00a7642f09b5b715"},
-]
-
-[package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
-
-[extras]
-core = ["accelerate", "datasets", "diffusers", "fire", "huggingface-hub", "instructor", "jsonlines", "poetry", "spacy", "torchmetrics", "transformers", "wandb", "weave"]
-docs = ["jupyter", "mkdocs", "mkdocs-glightbox", "mkdocs-jupyter", "mkdocs-material", "mkdocs-minify-plugin", "mkdocstrings"]
-
-[metadata]
-lock-version = "2.0"
-python-versions = "^3.10"
-content-hash = "ea40234059583011ea809df1b374a1e4fe7d7b37ee0210b70eaa34ac02f21001"
diff --git a/pyproject.toml b/pyproject.toml
index 1f7f906..1fdbb9a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,66 +1,51 @@
-[tool.poetry]
+[project]
 name = "hemm"
-version = "0.1.0"
+version = "0.2.0"
 description = ""
-authors = ["soumik12345 <19soumik.rakshit96@gmail.com>"]
 readme = "README.md"
-packages = [{ include = "hemm" }]
-
-[tool.poetry.dependencies]
-python = "^3.10"
-diffusers = "^0.27.2"
-accelerate = "^0.30.1"
-wandb = "^0.17.0"
-poetry = "^1.8.3"
-weave = "^0.50.9"
-huggingface-hub = "^0.23.0"
-datasets = "^2.19.1"
-fire = "^0.6.0"
-mkdocs = "^1.4.3"
-mkdocs-material = "^9.1.15"
-mkdocs-minify-plugin = "^0.6.4"
-mkdocs-glightbox = "^0.3.4"
-mkdocs-jupyter = "^0.24.1"
-jupyter = "^1.0.0"
-black = "^24.4.2"
-torcheval = "^0.0.7"
-ruff = "^0.4.5"
-openai = "^1.33.0"
-transformers = "^4.41.2"
-jsonlines = "^4.0.0"
-spacy = "^3.7.5"
-instructor = "^1.3.4"
-torchmetrics = { extras = ["multimodal"], version = "^1.4.1" }
-mkdocstrings = {version = "^0.25.2", extras = ["python"]}
-sentencepiece = "^0.2.0"
+requires-python = ">=3.10"
+dependencies = [
+    "diffusers>=0.30.3",
+    "accelerate>=1.0.1",
+    "huggingface-hub>=0.25.2",
+    "datasets>=3.0.1",
+    "fire>=0.7.0",
+    "fal_client>=0.5.0",
+    "instructor>=1.6.1",
+    "jsonlines>=4.0.0",
+    "openai>=1.51.2",
+    "sentencepiece>=0.2.0",
+    "torcheval>=0.0.7",
+    "torchmetrics[multimodal]>=1.4.1,<2.0.0",
+    "transformers>=4.45.2",
+    "spacy>=3.8.2",
+    "wandb>=0.18.3",
+    "weave==0.51.14",
+    "uv>=0.4.22",
+    "pip>=24.2",
+]
 
-[tool.poetry.extras]
-core = [
-    "diffusers",
-    "transformers",
-    "accelerate",
-    "wandb",
-    "weave",
-    "poetry",
-    "huggingface-hub",
-    "datasets",
-    "fire",
-    "jsonlines",
-    "spacy",
-    "instructor",
-    "torchmetrics",
-    "sentencepiece",
+[project.optional-dependencies]
+dev = [
+    "pytest>=8.3.3",
+    "isort>=5.13.2",
+    "black>=24.10.0",
+    "ruff>=0.6.9",
 ]
+
 docs = [
-    "mkdocs",
-    "mkdocstrings",
-    "mkdocs-material",
-    "mkdocs-minify-plugin",
-    "mkdocs-glightbox",
-    "mkdocs-jupyter",
-    "jupyter",
+    "mkdocs>=1.6.1",
+    "mkdocstrings>=0.26.1",
+    "mkdocstrings-python>=1.11.1",
+    "mkdocs-material>=9.5.39",
+    "mkdocs-minify-plugin>=0.8.0",
+    "mkdocs-glightbox>=0.4.0",
+    "mkdocs-jupyter>=0.25.0",
+    "jupyter>=1.1.1",
 ]
 
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"
\ No newline at end of file
+[tool.pytest.ini_options]
+pythonpath = "."
+
+[tool.setuptools]
+py-modules = ["hemm"]