Instructions to use NLPForUA/Llama-3.2-3B-Instruct-zno-cot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use NLPForUA/Llama-3.2-3B-Instruct-zno-cot with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.2-3B-Instruct") model = PeftModel.from_pretrained(base_model, "NLPForUA/Llama-3.2-3B-Instruct-zno-cot") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from NLPForUA/Llama-3.2-3B-Instruct-zno-cot: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/NLPForUA/Llama-3.2-3B-Instruct-zno-cot/resolve/main/tokenizer.json
- Command line
-
hf download hf://NLPForUA/Llama-3.2-3B-Instruct-zno-cot/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/NLPForUA/Llama-3.2-3B-Instruct-zno-cot/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 3e93ba348d7ce6513f3813ea521c1a387039326940439944c5bf9a12a11beeec
- Size of remote file:
- 17.2 MB
- SHA256:
- 89e7f2180ba598b166b631d64b2b2ba1d4fad8977a4c716b907c0eb2903f56a3
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