Instructions to use zeifar/mlm-miniLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zeifar/mlm-miniLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="zeifar/mlm-miniLM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("zeifar/mlm-miniLM") model = AutoModel.from_pretrained("zeifar/mlm-miniLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from zeifar/mlm-miniLM: direct link, hf CLI and curl.
- Browser
- Download file 471 MB
-
https://huggingface.co/zeifar/mlm-miniLM/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://zeifar/mlm-miniLM/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/zeifar/mlm-miniLM/resolve/main/pytorch_model.bin
471 MB
- Xet hash:
- 29409f88cb4b8d69ea2bff34a79298ce861dedf4bf8600e81fb51c37ae94b88e
- Size of remote file:
- 471 MB
- SHA256:
- 41c4be1cd39c8ca7f85ab7bf27cd014ad57e9c7a85fee62555eb6050cce5e6e5
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