Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use marcolatella/prova_Classi2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcolatella/prova_Classi2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcolatella/prova_Classi2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcolatella/prova_Classi2") model = AutoModelForSequenceClassification.from_pretrained("marcolatella/prova_Classi2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from marcolatella/prova_Classi2: direct link, hf CLI and curl.
- Browser
- Download file 2.93 kB
-
https://huggingface.co/marcolatella/prova_Classi2/resolve/main/training_args.bin
- Command line
-
hf download hf://marcolatella/prova_Classi2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/marcolatella/prova_Classi2/resolve/main/training_args.bin
2.93 kB
- Xet hash:
- 2f4301f34c7c8669bf44e36a5c7660d9e2fc4f8febd6d792a62f47a33ae2d10d
- Size of remote file:
- 2.93 kB
- SHA256:
- fd3ac6ff053f0a1764935387bd3e9c4da7044dbec344b4c6aba55178e8f56b6b
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