Instructions to use Raffix/THExtended_alpha_025 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raffix/THExtended_alpha_025 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Raffix/THExtended_alpha_025")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Raffix/THExtended_alpha_025") model = AutoModelForSequenceClassification.from_pretrained("Raffix/THExtended_alpha_025", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Raffix/THExtended_alpha_025: direct link, hf CLI and curl.
- Browser
- Download file 876 MB
-
https://huggingface.co/Raffix/THExtended_alpha_025/resolve/main/optimizer.pt
- Command line
-
hf download hf://Raffix/THExtended_alpha_025/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Raffix/THExtended_alpha_025/resolve/main/optimizer.pt
876 MB
- Xet hash:
- 25e279d998bab4d0aa40710361e0593954d03a3326c04edf2d6b18ea6cfaa766
- Size of remote file:
- 876 MB
- SHA256:
- da65827f4e2db08fc86de47c687544b8dc752743fcc76138f3da948ebcf5ec4e
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