Instructions to use aguglaniAI/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aguglaniAI/results with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("ybelkada/Mistral-7B-v0.1-bf16-sharded") model = PeftModel.from_pretrained(base_model, "aguglaniAI/results") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from aguglaniAI/results: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/aguglaniAI/results/resolve/main/training_args.bin
- Command line
-
hf download hf://aguglaniAI/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/aguglaniAI/results/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 57c382785da82e360e97544cdf9c87e4d4b18c4c437fd1b2a4b7be1e25331c1a
- Size of remote file:
- 4.73 kB
- SHA256:
- 282182954ffc8074acbbb1edc8b52accf1d03ceac4e2b5d28553c5808dc0df6a
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