Fill-Mask
Transformers
Safetensors
Portuguese
bert
feature-extraction
legal
licitação
editais
custom_code
Instructions to use tcepi/helbert-lsg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tcepi/helbert-lsg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tcepi/helbert-lsg", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("tcepi/helbert-lsg", trust_remote_code=True) model = AutoModel.from_pretrained("tcepi/helbert-lsg", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from tcepi/helbert-lsg: direct link, hf CLI and curl.
- Browser
- Download file 447 MB
-
https://huggingface.co/tcepi/helbert-lsg/resolve/main/model.safetensors
- Command line
-
hf download hf://tcepi/helbert-lsg/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/tcepi/helbert-lsg/resolve/main/model.safetensors
447 MB
- Xet hash:
- 27cd8da1be07e59676eedf0ec1106f884d8229ddfdcf438d6f56da369507798e
- Size of remote file:
- 447 MB
- SHA256:
- 9de9a52f100f83d6c51eaeeb4c4303834290885511367ea0be9bd89eadcd7b85
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