Instructions to use Volowan/MNLP_M3_rag_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Volowan/MNLP_M3_rag_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Volowan/MNLP_M3_rag_model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Volowan/MNLP_M3_rag_model") model = AutoModel.from_pretrained("Volowan/MNLP_M3_rag_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 933928d81695820013180947c4c78cd3b25d9a1768494b3a04f25741b0d44249
- Size of remote file:
- 2.38 GB
- SHA256:
- faabea57e7a0e6f3884387d8eaf75b1e727d425c1d902e2e1f17be6bbd8d2b0d
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