Sentence Similarity
sentence-transformers
TensorBoard
Safetensors
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use srsawant34/ProTopic-trial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use srsawant34/ProTopic-trial with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("srsawant34/ProTopic-trial") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use srsawant34/ProTopic-trial with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("srsawant34/ProTopic-trial") model = AutoModel.from_pretrained("srsawant34/ProTopic-trial", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-13/training_args.bin from srsawant34/ProTopic-trial: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/srsawant34/ProTopic-trial/resolve/main/checkpoint-13/training_args.bin
- Command line
-
hf download hf://srsawant34/ProTopic-trial/checkpoint-13/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/srsawant34/ProTopic-trial/resolve/main/checkpoint-13/training_args.bin
4.66 kB
- Xet hash:
- 559f32341feb7361538a18961393c9c18a9247400d91399803be35e8f8ddc760
- Size of remote file:
- 4.66 kB
- SHA256:
- a4a1df3583856d0db5b2bb774a763c87b2ace60f682a5953c2afa2d52293f931
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