Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
logistics
de-identification
Instructions to use flowxai/hazmatguard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/hazmatguard with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/hazmatguard")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/hazmatguard") model = AutoModelForTokenClassification.from_pretrained("flowxai/hazmatguard", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from flowxai/hazmatguard: direct link, hf CLI and curl.
- Browser
- Download file 598 MB
-
https://huggingface.co/flowxai/hazmatguard/resolve/main/model.safetensors
- Command line
-
hf download hf://flowxai/hazmatguard/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/flowxai/hazmatguard/resolve/main/model.safetensors
598 MB
- Xet hash:
- 3cf73d4a5a5035668fa90318454c616d35c409d5f3fe0f4b9276514867c4ba16
- Size of remote file:
- 598 MB
- SHA256:
- c506084a1935df349c0b350f78692fbfb62a2cd30cebf51d7e997cc96a7307ff
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