Instructions to use dada22231/af12f959-2447-4124-ba37-e9e3e6beee86 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/af12f959-2447-4124-ba37-e9e3e6beee86 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-Math-7B-Instruct") model = PeftModel.from_pretrained(base_model, "dada22231/af12f959-2447-4124-ba37-e9e3e6beee86") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dada22231/af12f959-2447-4124-ba37-e9e3e6beee86: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/dada22231/af12f959-2447-4124-ba37-e9e3e6beee86/resolve/main/training_args.bin
- Command line
-
hf download hf://dada22231/af12f959-2447-4124-ba37-e9e3e6beee86/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dada22231/af12f959-2447-4124-ba37-e9e3e6beee86/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 88a2b56d0966835da7f00918a3938bc128bc120f5b6f593a2b793e2c79b08bf5
- Size of remote file:
- 6.84 kB
- SHA256:
- 7218e6241d14ba52ca39ad4b66c181294f9cda922318afa804683d96602fcfc1
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