Instructions to use beyhan/checkpoint-3750 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beyhan/checkpoint-3750 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="beyhan/checkpoint-3750")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("beyhan/checkpoint-3750") model = AutoModelForTokenClassification.from_pretrained("beyhan/checkpoint-3750", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from beyhan/checkpoint-3750: direct link, hf CLI and curl.
- Browser
- Download file 885 MB
-
https://huggingface.co/beyhan/checkpoint-3750/resolve/main/optimizer.pt
- Command line
-
hf download hf://beyhan/checkpoint-3750/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/beyhan/checkpoint-3750/resolve/main/optimizer.pt
885 MB
- Xet hash:
- 2f21f55dcda67e4a79d11e07110889cb073f7ca031517c137adc0a088a0c1334
- Size of remote file:
- 885 MB
- SHA256:
- f91dc3e1b5a20602d0cb8aac5fda1271085d136f47ea56358bd84422f944e809
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