Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use osanseviero/trainer-chapter3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osanseviero/trainer-chapter3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="osanseviero/trainer-chapter3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("osanseviero/trainer-chapter3") model = AutoModelForSequenceClassification.from_pretrained("osanseviero/trainer-chapter3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from osanseviero/trainer-chapter3: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/osanseviero/trainer-chapter3/resolve/main/training_args.bin
- Command line
-
hf download hf://osanseviero/trainer-chapter3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/osanseviero/trainer-chapter3/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 3f1deb30f489836e7d4f4b77c267433148d32e1f908b0216d93e67468922358e
- Size of remote file:
- 4.03 kB
- SHA256:
- b5a97a8bd31d63e288f3f87ac9a3c28ecfbcf5db96abef0927042a1f3f456d4c
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