References: Share your work on the Hub

Source material

Source curriculum (structural mirror, cited as further study):
• Hugging Face, "LLM Course", Chapter 4: "Sharing models and tokenizers"
  Authors: the Hugging Face team (Lewis Tunstall, Leandro von Werra,
    Lysandre Debut, Sylvain Gugger, Merve Noyan, and others)
  Course page: https://huggingface.co/learn/llm-course/chapter4
  Code and notebooks: https://github.com/huggingface/course
  License: Apache 2.0 (prose and code)
  Required attribution: "Based on the Hugging Face LLM Course
    (huggingface.co/learn/llm-course), © Hugging Face, used under the
    Apache 2.0 license. This is an independent structural mirror;
    Hugging Face does not endorse it."
This lesson mirrors the structure of Chapter 4 (the Hub, the push_to_hub
API, the huggingface_hub library, the git/git-lfs workflow, and building a
model card). Clawdemy's lessons are original prose that follows the
pedagogical arc of the course. We do not reproduce or transcribe the
course; we cite it as the recommended companion. Course materials are used
under the Apache 2.0 license with the attribution above, which requires a
link to the license and an indication of changes, and does not permit
implying endorsement.

Read this next

• Hugging Face LLM Course, Chapter 4: Sharing models and tokenizers. The chapter this lesson mirrors. Its model-card section goes deeper on the structured metadata (tags, datasets, metrics) that makes a model discoverable, which is worth reading before you publish something you want others to find.

Going deeper

A short, durable list. Each link is a specific next step, not a generic pile.

• The huggingface_hub library docs. The full API behind push_to_hub: repo management, uploads, and the modern HTTP-based helpers. The reference for when you script Hub interactions.

• Model Cards documentation. What a complete model card contains and why, including the metadata header that powers Hub search and the dataset/metric links. The standard to aim for past the three-line minimum.

• The Hugging Face Hub guide. How repositories, versioning, and access control work on the Hub, including private repos and organizations. Useful once you are managing more than one model.

Adjacent topics

Where this connects inside the track.

• Fine-tune a pretrained model (lesson 3). This lesson publishes what you trained there. Passing push_to_hub=True in TrainingArguments is the direct bridge between the two.

• Wrangling data with the Datasets library (lesson 5). Phase 2 opens by turning to the data side. Datasets, like models, live on and load from the Hub with the same patterns you used here, so sharing carries straight over to data.