Instructions to use QyQy/VietAI-Assignment2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QyQy/VietAI-Assignment2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="QyQy/VietAI-Assignment2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("QyQy/VietAI-Assignment2") model = AutoModelForTokenClassification.from_pretrained("QyQy/VietAI-Assignment2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from QyQy/VietAI-Assignment2: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/QyQy/VietAI-Assignment2/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://QyQy/VietAI-Assignment2@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/QyQy/VietAI-Assignment2/resolve/refs%2Fpr%2F1/optimizer.pt
1.42 GB
- Xet hash:
- 9b41af5ef836d937f36c56d8af7bf617e693400d46a87f0c10c40b577266c90f
- Size of remote file:
- 1.42 GB
- SHA256:
- ffb6c02e6d14ee68cad2a512357446c010d4ff119037cbcf18db4ebc9c70989e
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