Instructions to use alchemist69/4af9ed1e-bd3a-483b-889b-badf5ae1616f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use alchemist69/4af9ed1e-bd3a-483b-889b-badf5ae1616f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "alchemist69/4af9ed1e-bd3a-483b-889b-badf5ae1616f") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from alchemist69/4af9ed1e-bd3a-483b-889b-badf5ae1616f: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/alchemist69/4af9ed1e-bd3a-483b-889b-badf5ae1616f/resolve/main/training_args.bin
- Command line
-
hf download hf://alchemist69/4af9ed1e-bd3a-483b-889b-badf5ae1616f/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/alchemist69/4af9ed1e-bd3a-483b-889b-badf5ae1616f/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- fa7584eb398d4ce6e4f1c56a19f7652d3492e4daa2187cc4f15737145b924f0f
- Size of remote file:
- 6.84 kB
- SHA256:
- c76d1c92a73e1b0a6d5b54711d74dae05af11fcef976fa0bac49f47e2138d80a
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