Instructions to use Raffix/THExtended_alpha_075 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raffix/THExtended_alpha_075 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Raffix/THExtended_alpha_075")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Raffix/THExtended_alpha_075") model = AutoModelForSequenceClassification.from_pretrained("Raffix/THExtended_alpha_075", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Raffix/THExtended_alpha_075: direct link, hf CLI and curl.
- Browser
- Download file 876 MB
-
https://huggingface.co/Raffix/THExtended_alpha_075/resolve/main/optimizer.pt
- Command line
-
hf download hf://Raffix/THExtended_alpha_075/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Raffix/THExtended_alpha_075/resolve/main/optimizer.pt
876 MB
- Xet hash:
- c3e664bd8931a41b614376d0d118db834e2c7047f7fdcf0a653860679a60598c
- Size of remote file:
- 876 MB
- SHA256:
- 51b691f658a6457ec564b342ae249796302dd2ddad92f4e79625051e214fcdd1
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