Sentence Similarity
sentence-transformers
PyTorch
Transformers
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use BlueAvenir/climeworks_use_case_updated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BlueAvenir/climeworks_use_case_updated with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BlueAvenir/climeworks_use_case_updated") 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 BlueAvenir/climeworks_use_case_updated with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BlueAvenir/climeworks_use_case_updated") model = AutoModel.from_pretrained("BlueAvenir/climeworks_use_case_updated", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_head.pkl from BlueAvenir/climeworks_use_case_updated: direct link, hf CLI and curl.
- Browser
- Download file 6.96 kB
-
https://huggingface.co/BlueAvenir/climeworks_use_case_updated/resolve/main/model_head.pkl
- Command line
-
hf download hf://BlueAvenir/climeworks_use_case_updated/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/BlueAvenir/climeworks_use_case_updated/resolve/main/model_head.pkl
6.96 kB
- Xet hash:
- ecca30994883c185745c472c08ef8bde10745e7a677d319f0fa096abb6fe4c4f
- Size of remote file:
- 6.96 kB
- SHA256:
- 18c842615e53baf1591300c9cf9905cd5f76b07f06cbb175f6aa30fcbbd1a87f
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