LLAMA3 doc update

python/sparknlp/annotator/seq2seq/llama3_transformer.py

@@ -20,13 +20,13 @@ class LLAMA3Transformer(AnnotatorModel, HasBatchedAnnotate, HasEngine):
     """Llama 3: Cutting-Edge Foundation and Fine-Tuned Chat Models
     
         The Llama 3 release introduces a new family of pretrained and fine-tuned LLMs, ranging in scale
-        from 1B to 70B parameters (1B, 3B, 7B, 13B, 34B, 70B). Llama 3 models are designed with enhanced
+        from 8B and 70B parameters. Llama 3 models are designed with enhanced
         efficiency, performance, and safety, making them more capable than previous versions. These models
         are trained on a more diverse and expansive dataset, offering improved contextual understanding 
         and generation quality.
     
-        The fine-tuned models, known as Llama 3-Chat, are optimized for dialogue applications using an advanced 
-        version of Reinforcement Learning from Human Feedback (RLHF). Llama 3-Chat models demonstrate superior 
+        The fine-tuned models, known as Llama 3-instruct, are optimized for dialogue applications using an advanced
+        version of Reinforcement Learning from Human Feedback (RLHF). Llama 3-instruct models demonstrate superior
         performance across multiple benchmarks, outperforming Llama 2 and even matching or exceeding the capabilities 
         of some closed-source models.
     

src/main/scala/com/johnsnowlabs/nlp/annotators/seq2seq/LLAMA3Transformer.scala

@@ -47,16 +47,17 @@ import org.json4s.jackson.JsonMethods._
 
 /** Llama 3: Cutting-Edge Foundation and Fine-Tuned Chat Models
   *
-  * The Llama 3 release introduces a new family of large language models, ranging from 1B to 70B
-  * parameters (1B, 3B, 7B, 13B, 34B, 70B). Llama 3 models are designed with a greater emphasis on
-  * efficiency, performance, and safety, achieving remarkable advancements in training and
-  * deployment processes. These models are trained on a diversified dataset that significantly
-  * enhances their capability to generate more accurate and contextually relevant outputs.
+  * The Llama 3 release introduces a new family of large language models, ranging from 8B to 70B
+  * parameters. Llama 3 models are designed with a greater emphasis on efficiency, performance,
+  * and safety, achieving remarkable advancements in training and deployment processes. These
+  * models are trained on a diversified dataset that significantly enhances their capability to
+  * generate more accurate and contextually relevant outputs.
   *
-  * The fine-tuned variants, known as Llama 3-Chat, are specifically optimized for dialogue-based
-  * applications, making use of Reinforcement Learning from Human Feedback (RLHF) with an advanced
-  * reward model. Llama 3-Chat models demonstrate state-of-the-art performance across multiple
-  * benchmarks and surpass the capabilities of Llama 2, particularly in conversational settings.
+  * The fine-tuned variants, known as Llama 3-instruct, are specifically optimized for
+  * dialogue-based applications, making use of Reinforcement Learning from Human Feedback (RLHF)
+  * with an advanced reward model. Llama 3-instruct models demonstrate state-of-the-art
+  * performance across multiple benchmarks and surpass the capabilities of Llama 2, particularly
+  * in conversational settings.
   *
   * Pretrained models can be loaded with `pretrained` of the companion object:
   * {{{