Instructions to use VinsmokeMir/Method_1_FineTuneONSC_OurModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VinsmokeMir/Method_1_FineTuneONSC_OurModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VinsmokeMir/Method_1_FineTuneONSC_OurModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VinsmokeMir/Method_1_FineTuneONSC_OurModel") model = AutoModelForSequenceClassification.from_pretrained("VinsmokeMir/Method_1_FineTuneONSC_OurModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from VinsmokeMir/Method_1_FineTuneONSC_OurModel: direct link, hf CLI and curl.
- Browser
- Download file 83.3 MB
-
https://huggingface.co/VinsmokeMir/Method_1_FineTuneONSC_OurModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://VinsmokeMir/Method_1_FineTuneONSC_OurModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/VinsmokeMir/Method_1_FineTuneONSC_OurModel/resolve/main/pytorch_model.bin
83.3 MB
- Xet hash:
- e62154cb814ac00563cd45a5a74f5a47f94e7d171aafb3226eaaf7dbf2b444d7
- Size of remote file:
- 83.3 MB
- SHA256:
- 274d2ec5ca2a6c6960e09922115a84f83ea658c92870fdc5d41a36039122a720
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