Feature Extraction
sentence-transformers
Safetensors
Model2Vec
static-embeddings
moderation
safety
abuse-detection
lf2
2bit-quantization
cpu-optimized
Instructions to use VTXAI/VTX-MOD-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use VTXAI/VTX-MOD-1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("VTXAI/VTX-MOD-1") 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] - Model2Vec
How to use VTXAI/VTX-MOD-1 with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("VTXAI/VTX-MOD-1") embeddings = model.encode(["It's dangerous to go alone!", "It's a secret to everybody."]) print(embeddings.shape) - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from VTXAI/VTX-MOD-1: direct link, hf CLI and curl.
- Browser
- Download file 131 MB
-
https://huggingface.co/VTXAI/VTX-MOD-1/resolve/main/model.safetensors
- Command line
-
hf download hf://VTXAI/VTX-MOD-1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/VTXAI/VTX-MOD-1/resolve/main/model.safetensors
131 MB
- Xet hash:
- 7d0152d737c767973b7c5642b5b15bcc398a75290208f541aa3c789241c0f1ff
- Size of remote file:
- 131 MB
- SHA256:
- d3d8907fe6ce29f77abc3522f693bdd87e42ac82c393b32474122a4092a88226
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