Instructions to use myhaaaaaaa/91082058-0b05-422a-9a6b-c18b808db69a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use myhaaaaaaa/91082058-0b05-422a-9a6b-c18b808db69a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("The-matt/llama2_ko-7b_distinctive-snowflake-182_1060") model = PeftModel.from_pretrained(base_model, "myhaaaaaaa/91082058-0b05-422a-9a6b-c18b808db69a") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from myhaaaaaaa/91082058-0b05-422a-9a6b-c18b808db69a: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/myhaaaaaaa/91082058-0b05-422a-9a6b-c18b808db69a/resolve/main/training_args.bin
- Command line
-
hf download hf://myhaaaaaaa/91082058-0b05-422a-9a6b-c18b808db69a/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/myhaaaaaaa/91082058-0b05-422a-9a6b-c18b808db69a/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- afd149d47cf1b656c25a800effd212211f01dfa2305784fb3ca499b2be7e1a96
- Size of remote file:
- 6.78 kB
- SHA256:
- c0bedff42b9c1fb867a49c8f9b94fd39a70b8166fa84d3cf236a9005c7410367
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