Text Classification
Transformers
TensorBoard
Safetensors
roberta
zero-shot
text-embeddings-inference
Instructions to use adriansanz/test5_balanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adriansanz/test5_balanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="adriansanz/test5_balanced")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("adriansanz/test5_balanced") model = AutoModelForSequenceClassification.from_pretrained("adriansanz/test5_balanced", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from adriansanz/test5_balanced: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/adriansanz/test5_balanced/resolve/main/training_args.bin
- Command line
-
hf download hf://adriansanz/test5_balanced/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/adriansanz/test5_balanced/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- d6f443065739b3d7b0a3c6598f78df98c1160c67281a277972a0067d6d12c953
- Size of remote file:
- 4.92 kB
- SHA256:
- c2fab25fe0fdb7c982cf6ad24395a6589fbf172bd61ec8df016c0d9614fda8e1
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