Instructions to use S2312dal/M1_MLM_cross with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use S2312dal/M1_MLM_cross with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="S2312dal/M1_MLM_cross")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("S2312dal/M1_MLM_cross") model = AutoModelForSequenceClassification.from_pretrained("S2312dal/M1_MLM_cross", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from S2312dal/M1_MLM_cross: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/S2312dal/M1_MLM_cross/resolve/main/training_args.bin
- Command line
-
hf download hf://S2312dal/M1_MLM_cross/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/S2312dal/M1_MLM_cross/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- 186425caec7dce05aed5c3c3cb0fabf1d374b2bdf233c4332ccef8f317116a29
- Size of remote file:
- 3.31 kB
- SHA256:
- c355b2a51bf6c9af2253d00c618ad523567bd7357682948505578a36e2e9f8f2
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