Instructions to use Paladiso/cde9c765-fb3c-47ac-9ba3-6a9cee6f5937 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Paladiso/cde9c765-fb3c-47ac-9ba3-6a9cee6f5937 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("01-ai/Yi-1.5-9B-Chat-16K") model = PeftModel.from_pretrained(base_model, "Paladiso/cde9c765-fb3c-47ac-9ba3-6a9cee6f5937") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Paladiso/cde9c765-fb3c-47ac-9ba3-6a9cee6f5937: direct link, hf CLI and curl.
- Browser
- Download file 6.9 kB
-
https://huggingface.co/Paladiso/cde9c765-fb3c-47ac-9ba3-6a9cee6f5937/resolve/main/training_args.bin
- Command line
-
hf download hf://Paladiso/cde9c765-fb3c-47ac-9ba3-6a9cee6f5937/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Paladiso/cde9c765-fb3c-47ac-9ba3-6a9cee6f5937/resolve/main/training_args.bin
6.9 kB
- Xet hash:
- 61c4e100a16489539365e9e11a0550939840675e53729962ec179dc55a7d4983
- Size of remote file:
- 6.9 kB
- SHA256:
- f89366f76e1fe8acf4ed4c62cc2644e7b98e1dde744b738458eac4e8b286e3d3
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