Instructions to use babblebots/initial-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use babblebots/initial-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("babblebots/initial-model") 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/initial-model with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("babblebots/initial-model") - Notebooks
- Google Colab
- Kaggle
Download model_head.pkl from babblebots/initial-model: direct link, hf CLI and curl.
- Browser
- Download file 19.3 kB
-
https://huggingface.co/babblebots/initial-model/resolve/refs%2Fpr%2F2/model_head.pkl
- Command line
-
hf download hf://babblebots/initial-model@refs/pr/2/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/babblebots/initial-model/resolve/refs%2Fpr%2F2/model_head.pkl
19.3 kB
- Xet hash:
- 5ac95d387437be9cfb476b31c44f7c2d45c2e5c58b051f3322d8aae2f86c8a80
- Size of remote file:
- 19.3 kB
- SHA256:
- cbb90cb7b21e073403c44811793d88d1d791b9d3b09cf539133622b02d6856df
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.