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
Denis2054/Transformers-for-NLP-2nd-Edition
View on GitHub ↗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
Transformers-for-NLP-2nd-Edition grew +0.1% in the last 30 days, ranks 68th of 203 in Fine-Tuning (LoRA / PEFT), last commit 1,026 days ago.
Star trajectory
126 days tracked+0.1% in 30d, above the Fine-Tuning (LoRA / PEFT) median of +0.1%.
Last commit 1,026 days ago, staler than the median of 260d.
How it compares in Fine-Tuning (LoRA / PEFT)
Ranked 68th of 203 by stars.
- Language
- Jupyter Notebook
- License
- MIT License
- Contributors
- 2
- Forks
- 360
- Watchers
- 18
- Open issues
- 2
- Releases
- 0
- Created
- 2022-03-03
- Stars this week
- +1
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