Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use S2312dal/M6_cross with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use S2312dal/M6_cross with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="S2312dal/M6_cross")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("S2312dal/M6_cross") model = AutoModelForSequenceClassification.from_pretrained("S2312dal/M6_cross", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from S2312dal/M6_cross: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/S2312dal/M6_cross/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://S2312dal/M6_cross/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/S2312dal/M6_cross/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 2e493e996bb8e3a1921019267cfc7ee69bb887ad0a8863cbc04532a3bb8d6de6
- Size of remote file:
- 438 MB
- SHA256:
- b24e011cfec005e59e9717ed74138ea07cbfae137636cb3cf76249a7f3aff9af
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