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 pytorch_model.bin from BlueAvenir/climeworks_use_case_updated: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/BlueAvenir/climeworks_use_case_updated/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://BlueAvenir/climeworks_use_case_updated/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/BlueAvenir/climeworks_use_case_updated/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- 15b303ca0e57d0b8594401415c0b38c94df03b7477c339ddcb103c7c643eeedb
- Size of remote file:
- 1.11 GB
- SHA256:
- ce33aeeaf9017cdd49da94c2d00902bea87e9155bd0abd36082174f2cd727d82
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