Introducing Llama 2: A New Generation of Language Models
Optimized for Dialogue and Conversational AI
Introducing Llama 2 Family of Models
Google AI has released the Llama 2 family of language models, a new generation of generative text models designed for various natural language processing (NLP) tasks, including dialogue and conversational AI.
The Llama 2 family encompasses a range of models, from small to large, with pretraining data token counts ranging from 7 billion to 140 billion. All models are trained with a global batch-size of 64.
Fine-tuned for Dialogue Use Cases
In addition to the pretrained models, Google AI has also released fine-tuned LLMs called Llama-2-Chat, which are specifically optimized for dialogue use cases. These models have been trained on a large dataset of dialogue data and are designed to generate human-like responses in various conversational scenarios.
Using Llama 2 in Your Applications
To use Llama 2 models in your applications, you can utilize the Hugging Face Transformers library. The following code snippet demonstrates how to import the library and instantiate a ChatModule instance for the "Llama-2-7b-chat-hf-q4f16_1-MLC" model:
```python import transformers # Import the ChatModule from Hugging Face Transformers from transformers import ChatModule # Instantiate a ChatModule instance for the "Llama-2-7b-chat-hf-q4f16_1-MLC" model chat_module = ChatModule.from_pretrained("Llama-2-7b-chat-hf-q4f16_1-MLC") ```You can then use the ChatModule instance to generate text and engage in conversations with the Llama 2 model.
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