# zyds/transformers-code

手把手带你实战 Huggingface Transformers 课程视频同步更新在B站与YouTube

Repository: https://github.com/zyds/transformers-code
Canonical: https://ross.abutalabs.com/products/transformers-code
Language: Jupyter Notebook
License Family: other
Topics: huggingface, peft, transformers
Last push: 2024-07-15T16:29:29+00:00

## Health v2 (maintenance only)
Score: 29/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 86
- inputs: {"age_days": 1211, "days_push": 779, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4053, forks 520 (observed 2026-08-28T04:08:33.891366+00:00)

## What it is
A hands-on course repository with Jupyter Notebook code accompanying a video series (on Bilibili and YouTube) for learning Hugging Face Transformers. It covers fundamentals, NLP task implementations, parameter-efficient fine-tuning with PEFT, low-precision training with bitsandbytes, and distributed training with accelerate.

## Use cases
- learn huggingface transformers from scratch
- fine-tune LLMs with LoRA and QLoRA
- practice NLP tasks like NER and text classification with transformers
- learn distributed training with accelerate and deepspeed
- train models in 8-bit or 4-bit precision
- follow a structured transformers tutorial with code

## When to choose
- you want a guided, video-backed course on the Hugging Face ecosystem
- you need practical notebooks covering PEFT methods like LoRA, P-tuning, and IA3
- you prefer Chinese-language instruction for transformers fine-tuning

## When to avoid
- you need production-ready library code rather than educational notebooks
- you require an officially licensed or maintained software package
- you only want English-language materials

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, llm-training, prompt-engineering
- domain: large-language-models, tutorials, deep-learning
- platform: python
- tags: huggingface-transformers, peft, lora, qlora, fine-tuning, jupyter-notebooks, chinese-language, video-course, natural-language-processing, gpu

## Member repositories
- zyds/transformers-code (main) score 29

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:33.891366+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:23:39.233955+00:00, confidence not recorded.
  - readme: https://github.com/zyds/transformers-code (fetched 2026-08-28T04:08:33.891366+00:00, sha 9facc76bd06a)
- Data as of 2026-08-30T08:39:29.467469+00:00.