Instructions to use bdatm-project/qwen-task2-zigzag-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bdatm-project/qwen-task2-zigzag-lora with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bdatm-project/qwen-task2-zigzag-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from bdatm-project/qwen-task2-zigzag-lora: direct link, hf CLI and curl.
- Browser
- Download file 20 MB
-
https://huggingface.co/bdatm-project/qwen-task2-zigzag-lora/resolve/main/tokenizer.json
- Command line
-
hf download hf://bdatm-project/qwen-task2-zigzag-lora/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/bdatm-project/qwen-task2-zigzag-lora/resolve/main/tokenizer.json
20 MB
- Xet hash:
- 85cab18e0b51bc39bc6fb27146abfccdb7290caa4cacb06f9d471df17910d56a
- Size of remote file:
- 20 MB
- SHA256:
- 5a41e6e9d92018a0d3b5dcdfc626e6563d993cef9c506928add7929b54a47e73
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