Sentence Similarity
sentence-transformers
TensorBoard
Safetensors
bert
feature-extraction
Trained with AutoTrain
text-embeddings-inference
Instructions to use clairedhx/autotrain-phe-avis-ct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use clairedhx/autotrain-phe-avis-ct with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("clairedhx/autotrain-phe-avis-ct") sentences = [ "search_query: i love autotrain", "search_query: huggingface auto train", "search_query: hugging face auto train", "search_query: i love autotrain" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download config_sentence_transformers.json from clairedhx/autotrain-phe-avis-ct: direct link, hf CLI and curl.
- Browser
- Download file 199 Bytes
-
https://huggingface.co/clairedhx/autotrain-phe-avis-ct/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://clairedhx/autotrain-phe-avis-ct/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/clairedhx/autotrain-phe-avis-ct/resolve/main/config_sentence_transformers.json
199 Bytes
| { | |
| "__version__": { | |
| "sentence_transformers": "3.3.1", | |
| "transformers": "4.47.1", | |
| "pytorch": "2.3.0" | |
| }, | |
| "prompts": {}, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |