Text Classification
setfit
Safetensors
sentence-transformers
new
generated_from_setfit_trainer
custom_code
text-embeddings-inference
Instructions to use tmp-org/dm_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use tmp-org/dm_v1 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("tmp-org/dm_v1") - sentence-transformers
How to use tmp-org/dm_v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tmp-org/dm_v1", trust_remote_code=True) 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
File size: 284 Bytes
9ae2cf4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"model_type": "SentenceTransformer",
"__version__": {
"sentence_transformers": "5.2.2",
"transformers": "4.57.1",
"pytorch": "2.10.0+cu128"
},
"prompts": {
"query": "",
"document": ""
},
"default_prompt_name": null,
"similarity_fn_name": "cosine"
} |