Text Generation
PEFT
Safetensors
English
super-mario-64
sm64
speedrun
tas
reasoning
qwen3
lora
unsloth
conversational
Instructions to use hugo74130/sm64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hugo74130/sm64 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen3-4b-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "hugo74130/sm64") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from hugo74130/sm64: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/hugo74130/sm64/resolve/main/tokenizer.json
- Command line
-
hf download hf://hugo74130/sm64/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/hugo74130/sm64/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 0317111ef90ab08a1f3668268a9a521b3f6a3450dd2970c330584b23c605dc01
- Size of remote file:
- 11.4 MB
- SHA256:
- 10ba4ba91270b1a50e5cd8e51023bccc66fc4ac4909dd7ae7ab29433411c9bb9
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