Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use zwellington/microtest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zwellington/microtest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zwellington/microtest")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zwellington/microtest") model = AutoModelForSequenceClassification.from_pretrained("zwellington/microtest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from zwellington/microtest: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/zwellington/microtest/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://zwellington/microtest/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/zwellington/microtest/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 28c5456d79a97c06f5292d28cd75e3d930772a0ed02084985a446a00021938c3
- Size of remote file:
- 438 MB
- SHA256:
- 905f8050bb07a80554bee17557c8cb8558f875d11b8168d8d2e9f0ce9d2a7bf7
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