Instructions to use Raneechu/mininglit2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Raneechu/mininglit2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "Raneechu/mininglit2") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Raneechu/mininglit2: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/Raneechu/mininglit2/resolve/main/training_args.bin
- Command line
-
hf download hf://Raneechu/mininglit2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Raneechu/mininglit2/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- 5c02d083ebeced33b2f45eefc96edb8608468672c5cdc728bf2c71f4cddfa61a
- Size of remote file:
- 5.05 kB
- SHA256:
- 7616e20ac45704a4c87f5d5b207b800f82788ba3ab5f193789f6463134e516b7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.