Sentence Similarity
sentence-transformers
Safetensors
Transformers
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use danfeg/ST-PARA-XLM-R-M_Finetuned-COMB-1500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use danfeg/ST-PARA-XLM-R-M_Finetuned-COMB-1500 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("danfeg/ST-PARA-XLM-R-M_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/ST-PARA-XLM-R-M_Finetuned-COMB-1500 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("danfeg/ST-PARA-XLM-R-M_Finetuned-COMB-1500") model = AutoModel.from_pretrained("danfeg/ST-PARA-XLM-R-M_Finetuned-COMB-1500", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from danfeg/ST-PARA-XLM-R-M_Finetuned-COMB-1500: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/danfeg/ST-PARA-XLM-R-M_Finetuned-COMB-1500/resolve/main/model.safetensors
- Command line
-
hf download hf://danfeg/ST-PARA-XLM-R-M_Finetuned-COMB-1500/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/danfeg/ST-PARA-XLM-R-M_Finetuned-COMB-1500/resolve/main/model.safetensors
1.11 GB
- Xet hash:
- b772e6956d3fc772f9fd35d67c5e9f8276207b7414322895c3baa699acc9ba00
- Size of remote file:
- 1.11 GB
- SHA256:
- a0e5b4f159f0815aed39027d14334bcf8ff2e9adc789be02e482e6eee26b93d8
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