Text Classification
setfit
Safetensors
sentence-transformers
xlm-roberta
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use vgarg/promo_prescriptive_28_04_2024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use vgarg/promo_prescriptive_28_04_2024 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("vgarg/promo_prescriptive_28_04_2024") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use vgarg/promo_prescriptive_28_04_2024 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vgarg/promo_prescriptive_28_04_2024") 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
Download tokenizer.json from vgarg/promo_prescriptive_28_04_2024: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/vgarg/promo_prescriptive_28_04_2024/resolve/main/tokenizer.json
- Command line
-
hf download hf://vgarg/promo_prescriptive_28_04_2024/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/vgarg/promo_prescriptive_28_04_2024/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 900d575674d5bfcd5c2b9059c9221a42f92c957ed7230f7e096d3e9580c3e4c2
- Size of remote file:
- 17.1 MB
- SHA256:
- 883b037111086fd4dfebbbc9b7cee11e1517b5e0c0514879478661440f137085
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