Text Classification
Transformers
Safetensors
camembert
Generated from Trainer
text-embeddings-inference
Instructions to use grexit-d/multipride_umberto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use grexit-d/multipride_umberto with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="grexit-d/multipride_umberto")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("grexit-d/multipride_umberto") model = AutoModelForSequenceClassification.from_pretrained("grexit-d/multipride_umberto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from grexit-d/multipride_umberto: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/grexit-d/multipride_umberto/resolve/main/training_args.bin
- Command line
-
hf download hf://grexit-d/multipride_umberto/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/grexit-d/multipride_umberto/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- 38f8e95b9ca0ae828f70799adb1f739b8e7679fc34e8d00ec0d227139a58045c
- Size of remote file:
- 5.84 kB
- SHA256:
- f1b545901f780e9402731fc9e060845d6aa62ce0b4cbcaad543824cc8a88daa2
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