Sentence Similarity
sentence-transformers
Safetensors
embedding_gemma2
embedding
multilingual
turkish
retrieval
audio
image
norovox
Instructions to use emrevrg/Nythos-Embed-Zero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use emrevrg/Nythos-Embed-Zero with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("emrevrg/Nythos-Embed-Zero") 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
Download preprocessor_config.json from emrevrg/Nythos-Embed-Zero: direct link, hf CLI and curl.
- Browser
- Download file 511 Bytes
-
https://huggingface.co/emrevrg/Nythos-Embed-Zero/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://emrevrg/Nythos-Embed-Zero/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/emrevrg/Nythos-Embed-Zero/resolve/main/preprocessor_config.json
511 Bytes
| { | |
| "dither": 0.0, | |
| "feature_extractor_type": "Gemma4AudioFeatureExtractor", | |
| "feature_size": 128, | |
| "fft_length": 512, | |
| "fft_overdrive": false, | |
| "frame_length": 320, | |
| "hop_length": 160, | |
| "input_scale_factor": 1.0, | |
| "max_frequency": 8000.0, | |
| "mel_floor": 0.001, | |
| "min_frequency": 0.0, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "per_bin_mean": null, | |
| "per_bin_stddev": null, | |
| "preemphasis": 0.0, | |
| "preemphasis_htk_flavor": true, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000 | |
| } | |