Instructions to use MindscapeRAG/MiA-Emb-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MindscapeRAG/MiA-Emb-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="MindscapeRAG/MiA-Emb-8B")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MindscapeRAG/MiA-Emb-8B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add pipeline tag and library name metadata
Verified signatureThis PR improves the model card by adding the `pipeline_tag: feature-extraction` and `library_name: transformers` to the YAML metadata. These additions help categorize the model correctly on the Hugging Face Hub and enable automated code snippets for users. The task type was identified from the `adapter_config.json` and the provided inference code.57f80e1
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upload the Embedding model: MiA-Emb-8B
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