Llama
llama.com- Category
- AI Tools
- Rank
- No. 193Tools index
- Pricing
- Open Source
- Type
- TOOL
- Builder
- meta-llama
- GitHub
- 59.6k stars
- Date
About
Meta's open-weight LLM family — 8B, 70B, and 405B parameter models for local and cloud inference.
What it does
This repository provides a compact Python implementation for loading Llama 2 checkpoints and generating text. It supports plain prompt completion and structured dialogue, with tokenization, sampling, attention caching, and multi-GPU model parallelism included.
Why it's ranked here
The code offers a direct, readable path from downloaded checkpoints to working inference. Its value is now mostly educational or compatibility-focused because Meta explicitly deprecated this repository and moved current development into several newer projects.
What's good
The implementation exposes core transformer mechanics instead of hiding them behind a hosted service. It includes pretrained and chat examples, batched generation, temperature and top-p controls, optional token probabilities, prompt-tag sanitization, and model-parallel loading.
Tradeoffs
Inference assumes CUDA, NCCL distributed setup, and hardware sized for the selected checkpoint shards. Model access requires license acceptance and approval. Chat prompts require exact formatting, safety classifiers remain the developer’s responsibility, and the repository is deprecated.
How to use it well
Use it to study or run Llama 2 inference on controlled GPU infrastructure, especially when transparent model code matters. Choose pretrained models for continuation tasks and tuned models for dialogue. Use the successor repositories for fine-tuning, safety tooling, recipes, or complete agent systems.
Technical notes+
setup.py packages the llama Python module and reads dependencies from requirements.txt: torch, fairscale, fire, and sentencepiece. llama/generation.py initializes NCCL, selects CUDA by LOCAL_RANK, matches checkpoint count to model-parallel size, loads params.json, and implements batched top-p or greedy generation. llama/model.py contains the transformer, rotary embeddings, grouped key-value handling, FairScale parallel layers, and preallocated CUDA caches. llama/tokenizer.py wraps SentencePiece. example_chat_completion.py and example_text_completion.py expose Fire-based command interfaces, while download.sh retrieves checkpoint shards and verifies checksums.
Observed
- License
- Llama 2 Community License with redistribution, acceptable-use, model-improvement, and large-service commercial conditions.
- Primary language
- Python, with a Bash script for model downloads.
- Packaging
- Installable as an editable setuptools package through pip.
- Dependencies
- PyTorch, FairScale, Fire, and SentencePiece.
- Interfaces
- Python library plus command-line chat and text-completion examples.
- Compute platform
- Inference initializes NCCL distributed processing and selects CUDA devices.
- Model access
- Checkpoint downloads require license acceptance and approval from Meta or Hugging Face.
- Repository status
- Deprecated in favor of separate model, safety, toolchain, agent-system, and cookbook repositories.
Read from README.md, setup.py, requirements.txt, example_chat_completion.py, example_text_completion.py, llama/model.py, llama/__init__.py, llama/tokenizer.py, llama/generation.py, LICENSE, UPDATES.md, download.sh, MODEL_CARD.md, USE_POLICY.md, CONTRIBUTING.md.
Intel on Llama
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