Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use S2312dal/M6_MLM_cross with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use S2312dal/M6_MLM_cross with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="S2312dal/M6_MLM_cross")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("S2312dal/M6_MLM_cross") model = AutoModelForSequenceClassification.from_pretrained("S2312dal/M6_MLM_cross", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from S2312dal/M6_MLM_cross: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/S2312dal/M6_MLM_cross/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://S2312dal/M6_MLM_cross/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/S2312dal/M6_MLM_cross/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 9e0686188e9bc2496dcd78e7eecd34aab49177c36f7e422f071dcceb86d4b628
- Size of remote file:
- 438 MB
- SHA256:
- 55c86f2f0ab85e5cae279e36ae2c69e2b56a8f74d8f3c0da526d17a4879ecdb9
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