Instructions to use MLMvsCLM/610m-mlm40-42k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MLMvsCLM/610m-mlm40-42k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="MLMvsCLM/610m-mlm40-42k", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MLMvsCLM/610m-mlm40-42k", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MLMvsCLM/610m-mlm40-42k: direct link, hf CLI and curl.
- Browser
- Download file 3.02 GB
-
https://huggingface.co/MLMvsCLM/610m-mlm40-42k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MLMvsCLM/610m-mlm40-42k/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MLMvsCLM/610m-mlm40-42k/resolve/main/pytorch_model.bin
3.02 GB
- Xet hash:
- 6c3d53cc1db8ac9ce37aeea31dd03d83741e8dc63be734be3a5ea9da9f302fd3
- Size of remote file:
- 3.02 GB
- SHA256:
- 4859f07d2d0069f99e264d426c342669d59b8324ee1d61e09088c17546908ebc
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