Sentence Similarity
sentence-transformers
Safetensors
qwen3
unsloth
feature-extraction
dense
text-embeddings-inference
Instructions to use samuerio/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use samuerio/model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("samuerio/model") 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] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use samuerio/model with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for samuerio/model to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for samuerio/model to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for samuerio/model to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="samuerio/model", max_seq_length=2048, )
- Xet hash:
- 432cc9754a9816f6f9ab534e2e16f175983369b4ee1fc794e08803f06475d2d9
- Size of remote file:
- 11.4 MB
- SHA256:
- ffca8caa339a6d5e207fe50a23eed785347f3e6befcdbb4deb3315c34a60a156
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