Feature Extraction
fse
Safetensors
English
static-embeddings
sentence-embeddings
gensim
paragram
word-embeddings
Instructions to use fse/paranmt-300-raw-float16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fse
How to use fse/paranmt-300-raw-float16 with fse:
pip install "fse>=2.0"
from fse import Encoder encoder = Encoder.from_pretrained("fse/paranmt-300-raw-float16") vectors = encoder.encode(["A sentence.", "Another sentence."]) - Notebooks
- Google Colab
- Kaggle
Download config.json from fse/paranmt-300-raw-float16: direct link, hf CLI and curl.
- Browser
- Download file 199 Bytes
-
https://huggingface.co/fse/paranmt-300-raw-float16/resolve/main/config.json
- Command line
-
hf download hf://fse/paranmt-300-raw-float16/config.json
-
curl -L -o config.json https://huggingface.co/fse/paranmt-300-raw-float16/resolve/main/config.json
199 Bytes
| { | |
| "fingerprint": "xxh3-128:26b7176aacbdf42b64c8e90791847319", | |
| "fse_config_version": 1, | |
| "fse_format_version": 1, | |
| "fse_kind": "encoder", | |
| "model": "model.safetensors", | |
| "model_type": "fse" | |
| } | |