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llama

Language
Python
Created
02/14/2023
Last updated
01/05/2024
License
Other
autowiki
Revision
0
Software Version
0.0.4Basic
Generated from
Commit
ef351e
Generated on
01/05/2024

Llama provides APIs and tooling for generating natural language text using large language models. The key functionality centers around the Llama class, which handles loading a pretrained model and providing methods to generate text continuations and conversational responses.

The Llama generator is built from model weights and a tokenizer located in llama. The weights implement an efficient transformer architecture, while the tokenizer handles encoding/decoding text using SentencePiece.

When built, the Llama instance exposes methods that take a prompt, feed it to the model token-by-token, and sample the next tokens to produce a completion. Additional methods provide easy-to-use interfaces for tasks like prompt finishing and dialog responses.

The llama examples show building a Llama generator and calling its methods to produce text for various prompts. Governance docs provide guidelines around intended use cases and contributions. The model card and documentation provide details on model training, evaluation, and deployment.

Overall, Llama focuses on providing a simple interface through the Llama class to generate text in a scalable and efficient way. The examples, governance, and documentation aim to promote safe and responsible application of the models.

Text Generation

References: llama, example_chat_completion.py, example_text_completion.py

This section covers text generation functionality for generating text continuations and chat responses. The Llama library provides two main interfaces for text generation - Llama generation methods for open-domain text, and a chat completion example that builds on the Llama class.

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Model

References: llama/model.py

The model code is contained within the …/model.py file. The hyperparameters for the model such as hidden size are defined.

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Tokenization

References: llama/tokenizer.py

The …/tokenizer.py file provides functionality for encoding and decoding text. It loads a SentencePiece model for tokenization from a specified file path on initialization.

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Text Generation Interface

References: llama/generation.py

The Llama class in the file …/generation.py provides a high-level API for generating text. The Llama class handles building and loading a pre-trained model.

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Governance

References: CODE_OF_CONDUCT.md, CONTRIBUTING.md, USE_POLICY.md

This section outlines the guidelines and policies for using and contributing to the Llama project. The CODE_OF_CONDUCT.md file establishes a code of conduct for inclusive, harassment-free participation. It describes responsibilities for maintainers to clarify standards and enforce the policy.

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Documentation

References: README.md, MODEL_CARD.md, UPDATES.md

The README.md file provides documentation on downloading and using the various Llama 2 models for text generation. It discusses important aspects like model sizes, required resources, quick start instructions, formatting requirements, licensing, and references for additional technical documentation.

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