Instructions to use 0x1202/67a992f4-04ea-4b25-84a9-4fc258302d90 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 0x1202/67a992f4-04ea-4b25-84a9-4fc258302d90 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "0x1202/67a992f4-04ea-4b25-84a9-4fc258302d90") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/trainer_state.json from 0x1202/67a992f4-04ea-4b25-84a9-4fc258302d90: direct link, hf CLI and curl.
- Browser
- Download file 5.69 kB
-
https://huggingface.co/0x1202/67a992f4-04ea-4b25-84a9-4fc258302d90/resolve/e1a3232bedf8bcb74c4c0d668edab0c97bd62879/last-checkpoint/trainer_state.json
- Command line
-
hf download hf://0x1202/67a992f4-04ea-4b25-84a9-4fc258302d90@e1a3232bedf8bcb74c4c0d668edab0c97bd62879/last-checkpoint/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/0x1202/67a992f4-04ea-4b25-84a9-4fc258302d90/resolve/e1a3232bedf8bcb74c4c0d668edab0c97bd62879/last-checkpoint/trainer_state.json
5.69 kB
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