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Hugging Face

As explained in Natural Language Processing in Action, Second Edition

Hugging Face Hub is an online repository and collaboration platform for sharing machine-learning models, datasets, and applications.

Hugging Face Hub is an online repository and collaboration platform for sharing machine-learning models, datasets, and applications. In practice, it provides downloadable model weights and access-controlled model pages for local experimentation. section 10.1.1

A typical local workflow includes:

  • Create an account and request access when a model has license restrictions. section 10.1.1

Loading Llama 2 locally

A Python workflow loads meta-llama/Llama-2-7b-chat-hf with LlamaTokenizer and LlamaForCausalLM, then generates an answer from tokenized prompt input.

How Natural Language Processing in Action, Second Edition covers it

How deep it goes
Explains authentication and model loading procedurally, but does not develop Hub-wide collaboration or dataset workflows.
Examples
Uses Llama 2 7B downloads, HF_TOKEN environment loading, prompt tokenization, and generated answers.
What it assumes
Assumes basic Python and environment handling while demonstrating token setup and model loading explicitly.
What you can do after
Operate/configure authenticated local model use with Hugging Face Hub and Transformers.
How it connects
Connects Hugging Face Hub with Llama 2, Transformers, tokenizers, causal language models, and access tokens.

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This explainer was generated by Manning's knowledge graph from the text of Natural Language Processing in Action, Second Edition. The section links point to the parts of the book it draws on.