Instructions to use Erland/Qwen-TTT-NLP701-Assignment2-Subtask3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Erland/Qwen-TTT-NLP701-Assignment2-Subtask3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Erland/Qwen-TTT-NLP701-Assignment2-Subtask3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from Erland/Qwen-TTT-NLP701-Assignment2-Subtask3: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Erland/Qwen-TTT-NLP701-Assignment2-Subtask3/resolve/main/tokenizer.json
- Command line
-
hf download hf://Erland/Qwen-TTT-NLP701-Assignment2-Subtask3/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Erland/Qwen-TTT-NLP701-Assignment2-Subtask3/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 4ac7a1f2d5dfc5e8ce17d1d222f0e825256ec129eab5b2b4076922d50a930b57
- Size of remote file:
- 11.4 MB
- SHA256:
- 4d865c53dde677f160d55bfe3ce66be84ff7e7702d487dd88cfcc268939f4e3f
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