Instructions to use fathyshalab/reklambox2-16-21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use fathyshalab/reklambox2-16-21 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("fathyshalab/reklambox2-16-21") 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 fathyshalab/reklambox2-16-21 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("fathyshalab/reklambox2-16-21") 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 fathyshalab/reklambox2-16-21: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/fathyshalab/reklambox2-16-21/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://fathyshalab/reklambox2-16-21/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fathyshalab/reklambox2-16-21/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- 70f902f45da920388a3c5da455b972487d03736e81be7a1aadc7b7bdb46c776e
- Size of remote file:
- 1.11 GB
- SHA256:
- a00712069f2092ff2bf786b3c84ee0815e1a738ce12f74e02889c8be98b984f6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.