Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use reyj1999/test_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reyj1999/test_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="reyj1999/test_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("reyj1999/test_model") model = AutoModelForSequenceClassification.from_pretrained("reyj1999/test_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from reyj1999/test_model: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/reyj1999/test_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://reyj1999/test_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/reyj1999/test_model/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- b9e562e03de22f86055ecfd1cbe2dd9596b2eeb77e7593a52c6ee24ff772c751
- Size of remote file:
- 268 MB
- SHA256:
- c9489817b78232b48d6251c593d018dbf79cd4982d66d412339559f47684fb89
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