Feature Extraction
Transformers
PyTorch
Hungarian
bert
BERT
encoder
embeddings
TiME
size:m
text-embeddings-inference
Instructions to use dschulmeist/TiME-hu-m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dschulmeist/TiME-hu-m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dschulmeist/TiME-hu-m")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dschulmeist/TiME-hu-m") model = AutoModel.from_pretrained("dschulmeist/TiME-hu-m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dschulmeist/TiME-hu-m: direct link, hf CLI and curl.
- Browser
- Download file 942 MB
-
https://huggingface.co/dschulmeist/TiME-hu-m/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dschulmeist/TiME-hu-m/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dschulmeist/TiME-hu-m/resolve/main/pytorch_model.bin
942 MB
- Xet hash:
- d67bd186abb6539d39ebd45ca5a2bcef30099e3b1d27c2b976e9bfb993ab4a8b
- Size of remote file:
- 942 MB
- SHA256:
- 92d853a7ab72adcc33f5320556e79218a57dcd76f4ef44c16675c5ce92db34b0
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