Instructions to use MindscapeRAG/MiA-Emb-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MindscapeRAG/MiA-Emb-4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="MindscapeRAG/MiA-Emb-4B")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MindscapeRAG/MiA-Emb-4B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add pipeline tag and library name to model card
Verified signatureHi! I'm Niels from the Hugging Face community team. This PR improves your model card's metadata by adding: - `pipeline_tag: feature-extraction`: This helps users find your model when filtering by task on the Hub. - `library_name: transformers`: This enables an automated code snippet on the model page, showcasing how to use the model with the Transformers library. The rest of the model card remains unchanged.a350e93
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Update README.md
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Delete training_args.bin
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Upload Embedding model: MiA-Emb-4B version
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initial commit
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