Instructions to use DJHumanRPT/test_gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DJHumanRPT/test_gguf with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B-Instruct") model = PeftModel.from_pretrained(base_model, "DJHumanRPT/test_gguf") - Notebooks
- Google Colab
- Kaggle
Download base_model/tokenizer.json from DJHumanRPT/test_gguf: direct link, hf CLI and curl.
- Browser
- Download file 9.09 MB
-
https://huggingface.co/DJHumanRPT/test_gguf/resolve/main/base_model/tokenizer.json
- Command line
-
hf download hf://DJHumanRPT/test_gguf/base_model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/DJHumanRPT/test_gguf/resolve/main/base_model/tokenizer.json
9.09 MB
- Xet hash:
- 5cdea387e5b8478fd9d75abfa38e9ec5fdd6c2bf542a433c3cb4e487d5d44323
- Size of remote file:
- 9.09 MB
- SHA256:
- 79e3e522635f3171300913bb421464a87de6222182a0570b9b2ccba2a964b2b4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.