Text Classification
sentence-transformers
Safetensors
English
model_hub_mixin
pytorch_model_hub_mixin
Instructions to use Gyaneshere/sbert_mlp_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Gyaneshere/sbert_mlp_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Gyaneshere/sbert_mlp_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] - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Gyaneshere/sbert_mlp_model: direct link, hf CLI and curl.
- Browser
- Download file 411 kB
-
https://huggingface.co/Gyaneshere/sbert_mlp_model/resolve/main/model.safetensors
- Command line
-
hf download hf://Gyaneshere/sbert_mlp_model/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Gyaneshere/sbert_mlp_model/resolve/main/model.safetensors
411 kB
- Xet hash:
- 7ba88e096822f7c7da7522361bb7615a9158d04fb661fa56f41aa100873f1f53
- Size of remote file:
- 411 kB
- SHA256:
- 3909048e8eccda0a4378aad329bb0298eea29bc968ace8ae75cdf05c7c453b5e
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