Llama 2 7B Chat Model Overview

This model is the 7 billion parameter variant of Meta's Llama 2 family, specifically fine-tuned for dialogue applications and converted for Hugging Face Transformers. Llama 2 models are auto-regressive language models utilizing an optimized transformer architecture. The chat-optimized versions, known as Llama-2-Chat, are aligned to human preferences for helpfulness and safety through supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF).

Key Capabilities & Features

Dialogue Optimization: Specifically fine-tuned for assistant-like chat interactions.
Performance: Outperforms many open-source chat models on various benchmarks and achieves parity with some popular closed-source models like ChatGPT and PaLM in human evaluations for helpfulness and safety.
Context Length: Supports a 4096-token context window.
Training Data: Pretrained on 2 trillion tokens from publicly available sources, with fine-tuning data including over one million human-annotated examples.
Safety: Evaluated for safety, with the 7B chat model achieving 0.00% toxic generations on the ToxiGen benchmark.

Intended Use Cases

Commercial and Research Use: Primarily intended for English-language applications.
Assistant-like Chat: Ideal for building conversational AI agents and chatbots.

Limitations

English Only: Performance is not guaranteed for languages other than English.
Potential for Objectionable Content: Like all LLMs, it may produce inaccurate, biased, or objectionable responses, requiring developers to perform safety testing and tuning for specific applications.
Licensing: Use is governed by a custom commercial license from Meta, requiring acceptance before access.