Instructions to use PranavBP525/slava with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use PranavBP525/slava with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("liuhaotian/llava-v1.5-7b") model = PeftModel.from_pretrained(base_model, "PranavBP525/slava") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from PranavBP525/slava: direct link, hf CLI and curl.
- Browser
- Download file 17.5 MB
-
https://huggingface.co/PranavBP525/slava/resolve/main/tokenizer.json
- Command line
-
hf download hf://PranavBP525/slava/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/PranavBP525/slava/resolve/main/tokenizer.json
17.5 MB
- Xet hash:
- 8e8ea5064e9de04387325e8131031d8d8b05f534c4ee9161e346e689556be031
- Size of remote file:
- 17.5 MB
- SHA256:
- a2d9fb459fbdb6aa13b3d5f2959560e79e00009d77ef8974e82d022790f36ed0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.