Instructions to use dimasik87/ed20e542-9648-402a-845b-f096cbb99cfc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/ed20e542-9648-402a-845b-f096cbb99cfc with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("echarlaix/tiny-random-mistral") model = PeftModel.from_pretrained(base_model, "dimasik87/ed20e542-9648-402a-845b-f096cbb99cfc") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dimasik87/ed20e542-9648-402a-845b-f096cbb99cfc: direct link, hf CLI and curl.
- Browser
- Download file 6.71 kB
-
https://huggingface.co/dimasik87/ed20e542-9648-402a-845b-f096cbb99cfc/resolve/main/training_args.bin
- Command line
-
hf download hf://dimasik87/ed20e542-9648-402a-845b-f096cbb99cfc/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dimasik87/ed20e542-9648-402a-845b-f096cbb99cfc/resolve/main/training_args.bin
6.71 kB
- Xet hash:
- 0e67fbb4833ee73f9a6aeeda97319029cdc7b5f8b204d805e33b347330ae7158
- Size of remote file:
- 6.71 kB
- SHA256:
- 886be391b44d3aeb529cc28ffccc412a8abd1023317eaf0bcd19315e5119ab70
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