Instructions to use 1337Hero/qwen3-coder-30b-a3b-codemonkey with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 1337Hero/qwen3-coder-30b-a3b-codemonkey with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen3-coder-30b-a3b-instruct") model = PeftModel.from_pretrained(base_model, "1337Hero/qwen3-coder-30b-a3b-codemonkey") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from 1337Hero/qwen3-coder-30b-a3b-codemonkey: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/1337Hero/qwen3-coder-30b-a3b-codemonkey/resolve/main/tokenizer.json
- Command line
-
hf download hf://1337Hero/qwen3-coder-30b-a3b-codemonkey/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/1337Hero/qwen3-coder-30b-a3b-codemonkey/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- a3e80a0c7329b91f5fce702283fd80864a9012820ce5d04b832359d0955ba1f0
- Size of remote file:
- 11.4 MB
- SHA256:
- 45c4ffda6666cf6d75d0b1f961f25964e2a52a62e78aaecb2f458e9ba9824112
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.