diff --git a/python/sparknlp/annotator/seq2seq/llama3_transformer.py b/python/sparknlp/annotator/seq2seq/llama3_transformer.py index 41313b49d67ff6..43b32f1a70454a 100644 --- a/python/sparknlp/annotator/seq2seq/llama3_transformer.py +++ b/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. diff --git a/src/main/scala/com/johnsnowlabs/nlp/annotators/seq2seq/LLAMA3Transformer.scala b/src/main/scala/com/johnsnowlabs/nlp/annotators/seq2seq/LLAMA3Transformer.scala index c0d2431c2f3e3d..1eecc75c557e26 100644 --- a/src/main/scala/com/johnsnowlabs/nlp/annotators/seq2seq/LLAMA3Transformer.scala +++ b/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: * {{{