Text Classification
ONNX
sentence-transformers
French
English
yes-no
intent-classification
distillation
edge
quantization
Eval Results (legacy)
Instructions to use jcfossati/ForSureLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jcfossati/ForSureLLM with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jcfossati/ForSureLLM") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Download forsurellm-int8_fr-en.onnx from jcfossati/ForSureLLM: direct link, hf CLI and curl.
- Browser
- Download file 24.3 MB
-
https://huggingface.co/jcfossati/ForSureLLM/resolve/main/forsurellm-int8_fr-en.onnx
- Command line
-
hf download hf://jcfossati/ForSureLLM/forsurellm-int8_fr-en.onnx
-
curl -L -o forsurellm-int8_fr-en.onnx https://huggingface.co/jcfossati/ForSureLLM/resolve/main/forsurellm-int8_fr-en.onnx
24.3 MB
- Xet hash:
- 6f5eb5c5f996a6cd9566caf6a9ec309ca7fd22546a82a8b4eae611ec7a32e57e
- Size of remote file:
- 24.3 MB
- SHA256:
- 81f71d7044c23800bb52751e7eb73ecbcf32f8c77e8528200d006ab777bbd362
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