Instructions to use togethercomputer/m2-bert-80M-8k-retrieval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use togethercomputer/m2-bert-80M-8k-retrieval with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("togethercomputer/m2-bert-80M-8k-retrieval", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from togethercomputer/m2-bert-80M-8k-retrieval: direct link, hf CLI and curl.
- Browser
- Download file 351 MB
-
https://huggingface.co/togethercomputer/m2-bert-80M-8k-retrieval/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://togethercomputer/m2-bert-80M-8k-retrieval/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/togethercomputer/m2-bert-80M-8k-retrieval/resolve/main/pytorch_model.bin
351 MB
- Xet hash:
- d0a7bafeb88b92807afd4f332edd277c4a4afd7d3eafe70e2629b64db261d0d3
- Size of remote file:
- 351 MB
- SHA256:
- e2b81f81f855d9f9cfeb6fd0eda2d502743d48ac91908f33657c6293d6abf235
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