Instructions to use felixml/genre_pred_model_balanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use felixml/genre_pred_model_balanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="felixml/genre_pred_model_balanced")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("felixml/genre_pred_model_balanced") model = AutoModelForSequenceClassification.from_pretrained("felixml/genre_pred_model_balanced", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from felixml/genre_pred_model_balanced: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/felixml/genre_pred_model_balanced/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://felixml/genre_pred_model_balanced/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/felixml/genre_pred_model_balanced/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 81acdc7a455b6204c75231a9aa62f5ce28e3b12070abd4a18f0602d48f4fac41
- Size of remote file:
- 268 MB
- SHA256:
- 89a6fe5832ce412b5c9b3584970484c5678b91a6c23f5dfc32a803d8bb1b0a30
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