Instructions to use pgilliar/MNLP_M2_rag_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pgilliar/MNLP_M2_rag_model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pgilliar/MNLP_M2_rag_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6602c54086b6b25bc565db2140cd11aba95d919e14cfd8a31e488372db1508d
- Size of remote file:
- 117 Bytes
- SHA256:
- 28396d421a2108acce96383f6a7de78008f7f1b17f807958f3c14c51dbfb65fb
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