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 optimizer.pt from Raffix/THExtended_alpha_0: direct link, hf CLI and curl.
- Browser
- Download file 876 MB
-
https://huggingface.co/Raffix/THExtended_alpha_0/resolve/main/optimizer.pt
- Command line
-
hf download hf://Raffix/THExtended_alpha_0/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Raffix/THExtended_alpha_0/resolve/main/optimizer.pt
876 MB
- Xet hash:
- 7d1f94d37da05a36a81dd3f1669512865e9062cf9217c0d9127327f0b0d5b202
- Size of remote file:
- 876 MB
- SHA256:
- 151c9a14c8847d45b710f5bae059234e00b5a72431c9c4e87a34b6e092de0d9e
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