Denis2054/Transformers-for-NLP-2nd-Edition

Transformer models from BERT to GPT-4, environments from Hugging Face to OpenAI. Fine-tuning, training, and prompt engineering examples. A bonus section with ChatGPT, GPT-3.5-turbo, GPT-4, and DALL-E including jump starting GPT-4, speech-to-text, text-to-speech, text to image generation with DALL-E, Google Cloud AI,HuggingGPT, and more

960 357 +0/wk

GitHub

bert chatgpt chatgpt-api dall-e dall-e-api deep-learning gpt-3-5-turbo gpt-4 gpt-4-api huggingface-transformers machine-learning natural-language-processing

Trend 3

Star & Fork Trend (42 data points)

Stars

Forks

Multi-Source Signals

GitHub

stars 960

forks 357

Growth Velocity

Denis2054/Transformers-for-NLP-2nd-Edition has +0 stars this period . 7-day velocity: 0.1%.

Deep analysis is being generated for this repository.

Signal-backed technical analysis will be available soon.

Metric	Transformers-for-NLP-2nd-Edition	Coursera-ML-using-matlab-python	FlashRank	machine-learning-toy-code
Stars	960	960	960	959
Forks	357	366	69	196
Weekly Growth	+0	+0	+2	+0
Language	Jupyter Notebook	Jupyter Notebook	Python	Jupyter Notebook
Sources	1	1	1	1
License	MIT	N/A	Apache-2.0	MIT

Capability Radar vs Coursera-ML-using-matlab-python

Transformers-for-NLP-2nd-Edition

Coursera-ML-using-matlab-python

Maintenance Activity 0

Last code push 825 days ago.

Community Engagement 100

Fork-to-star ratio: 37.2%. Active community forking and contributing.

Issue Burden 70

Issue data not yet available.

Growth Momentum 30

No measurable growth in the current period (first-day cold start expected).

License Clarity 95

Licensed under MIT. Permissive — safe for commercial use.

Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.