Feature Extraction
Transformers
Safetensors
English
base_encoder
scientific-retrieval
dense-passage-retrieval
dual-encoder
talk2ref
speech-to-text
sentence-embedding
SBERT
Instructions to use s8frbroy/talk2ref_query_talk_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use s8frbroy/talk2ref_query_talk_encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="s8frbroy/talk2ref_query_talk_encoder")# Load model directly from transformers import BaseEncoderHF model = BaseEncoderHF.from_pretrained("s8frbroy/talk2ref_query_talk_encoder", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38a8699c02245517fd1b0901b6417bda4bde6250edd9b7cca28bb4a3860bb770
- Size of remote file:
- 91 MB
- SHA256:
- bbad54f4fc9c00ea3de10d9f8e3a46de8d3152ed97bf20e0c16317362d154327
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