Instructions to use Volowan/MNLP_M2_document_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Volowan/MNLP_M2_document_encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Volowan/MNLP_M2_document_encoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Volowan/MNLP_M2_document_encoder") model = AutoModel.from_pretrained("Volowan/MNLP_M2_document_encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Volowan/MNLP_M2_document_encoder: direct link, hf CLI and curl.
- Browser
- Download file 133 MB
-
https://huggingface.co/Volowan/MNLP_M2_document_encoder/resolve/main/model.safetensors
- Command line
-
hf download hf://Volowan/MNLP_M2_document_encoder/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Volowan/MNLP_M2_document_encoder/resolve/main/model.safetensors
133 MB
- Xet hash:
- 3e0429be0d5858b6149840861daec1cff1bebdd7f56c81ea361d0db067998def
- Size of remote file:
- 133 MB
- SHA256:
- ea1d11a3f23d14fe09fc1826fc7944e89c09a634d2217d57a21dd136805ee3e8
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