Instructions to use koenvdv/my-test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use koenvdv/my-test-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="koenvdv/my-test-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("koenvdv/my-test-model") model = AutoModelForSequenceClassification.from_pretrained("koenvdv/my-test-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from koenvdv/my-test-model: direct link, hf CLI and curl.
- Browser
- Download file 329 MB
-
https://huggingface.co/koenvdv/my-test-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://koenvdv/my-test-model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/koenvdv/my-test-model/resolve/main/pytorch_model.bin
329 MB
- Xet hash:
- e4be3e77c3de5424fc1657564de0f0d7befa2eb66fa8b02573713b42b0d9d76a
- Size of remote file:
- 329 MB
- SHA256:
- e0aa4545a419a359f3b2e4c82d02b656beb85db77ab92cfe58983bd8fc50e0a0
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