Instructions to use tuandunghcmut/Qwen25_Coder_MultipleChoice_v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tuandunghcmut/Qwen25_Coder_MultipleChoice_v4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen2.5-coder-1.5b-instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "tuandunghcmut/Qwen25_Coder_MultipleChoice_v4") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from tuandunghcmut/Qwen25_Coder_MultipleChoice_v4: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/tuandunghcmut/Qwen25_Coder_MultipleChoice_v4/resolve/main/tokenizer.json
- Command line
-
hf download hf://tuandunghcmut/Qwen25_Coder_MultipleChoice_v4/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/tuandunghcmut/Qwen25_Coder_MultipleChoice_v4/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 18f5ee8c52e9d225044dd7ef664f390226accb3a4e27ac5d3e5a71e8a4eebf2a
- Size of remote file:
- 11.4 MB
- SHA256:
- fab42efe8d17406525a9154b728cf9e957629a8ed7ce997770efdd71128c6a1a
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