Instructions to use Raffix/THExtended_alpha_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raffix/THExtended_alpha_0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Raffix/THExtended_alpha_0")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Raffix/THExtended_alpha_0") model = AutoModelForSequenceClassification.from_pretrained("Raffix/THExtended_alpha_0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Raffix/THExtended_alpha_0: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/Raffix/THExtended_alpha_0/resolve/main/training_args.bin
- Command line
-
hf download hf://Raffix/THExtended_alpha_0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Raffix/THExtended_alpha_0/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- f655b1e50be645d0482e29bdebcd41592e65bdb66ce984b75306f9b183a24add
- Size of remote file:
- 3.96 kB
- SHA256:
- 58c9561217802554c324e3dd3c31ba281dae6c10d7fa546a4763d8bb9708ead5
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