Instructions to use Raffix/THExtended_alpha_05 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raffix/THExtended_alpha_05 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Raffix/THExtended_alpha_05")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Raffix/THExtended_alpha_05") model = AutoModelForSequenceClassification.from_pretrained("Raffix/THExtended_alpha_05", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Raffix/THExtended_alpha_05: direct link, hf CLI and curl.
- Browser
- Download file 876 MB
-
https://huggingface.co/Raffix/THExtended_alpha_05/resolve/main/optimizer.pt
- Command line
-
hf download hf://Raffix/THExtended_alpha_05/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Raffix/THExtended_alpha_05/resolve/main/optimizer.pt
876 MB
- Xet hash:
- 644d32fe01604221bba7e999f5310f294bd75f5ac3c7e4b6c230c3ecc7ecdc0d
- Size of remote file:
- 876 MB
- SHA256:
- 02cb95506831659b305c7d88c911609422d6b2f4a7265b270ce5b228e0db1014
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