Instructions to use Siddartha10/llama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Siddartha10/llama with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "Siddartha10/llama") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from Siddartha10/llama: direct link, hf CLI and curl.
- Browser
- Download file 9.09 MB
-
https://huggingface.co/Siddartha10/llama/resolve/main/tokenizer.json
- Command line
-
hf download hf://Siddartha10/llama/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Siddartha10/llama/resolve/main/tokenizer.json
9.09 MB
- Xet hash:
- 5cdea387e5b8478fd9d75abfa38e9ec5fdd6c2bf542a433c3cb4e487d5d44323
- Size of remote file:
- 9.09 MB
- SHA256:
- 79e3e522635f3171300913bb421464a87de6222182a0570b9b2ccba2a964b2b4
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