Instructions to use Intel/bge-base-en-v1.5-rag-int8-static with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/bge-base-en-v1.5-rag-int8-static with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Intel/bge-base-en-v1.5-rag-int8-static")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Intel/bge-base-en-v1.5-rag-int8-static") model = AutoModel.from_pretrained("Intel/bge-base-en-v1.5-rag-int8-static", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef6576dced4493103a285b6c13798f6a95249c3c98f98ff336e252e4cf4a5718
- Size of remote file:
- 134 MB
- SHA256:
- fa4f569abb09c38218dfffffb479916dfd0432ea5d0697416af1505932d59e85
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