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 config.json from VTXAI/VTX-MOD-1: direct link, hf CLI and curl.
- Browser
- Download file 324 Bytes
-
https://huggingface.co/VTXAI/VTX-MOD-1/resolve/01ded0f958b3da983a232551150c52ef9e4e540f/config.json
- Command line
-
hf download hf://VTXAI/VTX-MOD-1@01ded0f958b3da983a232551150c52ef9e4e540f/config.json
-
curl -L -o config.json https://huggingface.co/VTXAI/VTX-MOD-1/resolve/01ded0f958b3da983a232551150c52ef9e4e540f/config.json
324 Bytes
| { | |
| "model_type": "model2vec", | |
| "architectures": [ | |
| "StaticModel" | |
| ], | |
| "tokenizer_name": "VTXAI/vtx-jev-mod-multilingual", | |
| "apply_pca": 256, | |
| "sif_coefficient": 0.0001, | |
| "hidden_dim": 256, | |
| "seq_length": 1000000, | |
| "normalize": true, | |
| "pooling": "mean", | |
| "embedding_dtype": "float16" | |
| } |