Instructions to use babblebots/short-answer-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use babblebots/short-answer-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("babblebots/short-answer-v1") 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] - setfit
How to use babblebots/short-answer-v1 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("babblebots/short-answer-v1") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from babblebots/short-answer-v1: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/babblebots/short-answer-v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://babblebots/short-answer-v1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/babblebots/short-answer-v1/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 22087f40a7e3e51a891caf59c344f15aa772eb161727495f860d23cd813380ad
- Size of remote file:
- 438 MB
- SHA256:
- e5ca907b60241ad56b04a3147794915133fbdf64cf47e4b4dbb5a4867da5ba1a
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