Sentence Similarity
sentence-transformers
Safetensors
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use danfeg/CAMeL_Finetuned-COMB-1500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use danfeg/CAMeL_Finetuned-COMB-1500 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("danfeg/CAMeL_Finetuned-COMB-1500") 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] - Transformers
How to use danfeg/CAMeL_Finetuned-COMB-1500 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("danfeg/CAMeL_Finetuned-COMB-1500") model = AutoModel.from_pretrained("danfeg/CAMeL_Finetuned-COMB-1500", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from danfeg/CAMeL_Finetuned-COMB-1500: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/danfeg/CAMeL_Finetuned-COMB-1500/resolve/main/model.safetensors
- Command line
-
hf download hf://danfeg/CAMeL_Finetuned-COMB-1500/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/danfeg/CAMeL_Finetuned-COMB-1500/resolve/main/model.safetensors
436 MB
- Xet hash:
- 2483d174cff11cc9763c2cefce215618f41b4bbe33dd025fd5f065ba7dfe89e9
- Size of remote file:
- 436 MB
- SHA256:
- 3e6aa9049b35a3bc98aa18e975466979366d2468c9de6326598779b405ce1b80
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