Instructions to use MindscapeRAG/MiA-Emb-0.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MindscapeRAG/MiA-Emb-0.6B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="MindscapeRAG/MiA-Emb-0.6B")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MindscapeRAG/MiA-Emb-0.6B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 492c1b6cea42efb14670cb811e6331166e9c6c89c06843e254f9125859a6f89f
- Size of remote file:
- 73.4 MB
- SHA256:
- b5b4289838cf7c0a840bd8f1e557151908546d2fa29fa3f4923b30246bf63a5d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.