Sentence Similarity
sentence-transformers
PyTorch
roberta
feature-extraction
text-embeddings-inference
Instructions to use seanfarrell/set_fit_experiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use seanfarrell/set_fit_experiment with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("seanfarrell/set_fit_experiment") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download model_head.pkl from seanfarrell/set_fit_experiment: direct link, hf CLI and curl.
- Browser
- Download file 403 kB
-
https://huggingface.co/seanfarrell/set_fit_experiment/resolve/main/model_head.pkl
- Command line
-
hf download hf://seanfarrell/set_fit_experiment/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/seanfarrell/set_fit_experiment/resolve/main/model_head.pkl
403 kB
- Xet hash:
- 49f55151adde8412a538e8f76aeaf64188f91d503dc1d09ad8f2cc09f4236130
- Size of remote file:
- 403 kB
- SHA256:
- 91973e13b91a15bc8ee8f75c04e443641b0dad25613479e4c471289db32a09cc
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