Instructions to use roscazo/DISO_bsc_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roscazo/DISO_bsc_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="roscazo/DISO_bsc_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("roscazo/DISO_bsc_test") model = AutoModelForTokenClassification.from_pretrained("roscazo/DISO_bsc_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from roscazo/DISO_bsc_test: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/roscazo/DISO_bsc_test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://roscazo/DISO_bsc_test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/roscazo/DISO_bsc_test/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- fccbef81364c902ea87e77ec38f611ab7f2f2f36d58db0fdb2183213b29b7df0
- Size of remote file:
- 496 MB
- SHA256:
- 5b90e7b18aef93dbea0e61d04854f9a0ab263e3068b523b37e04d895803fbb6e
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