Transformers
Safetensors
English
text-generation-inference
unsloth
qwen2
trl
How to use from
Unsloth Studio
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for xtremecoder/Qwen2.5-Coder-7B-Instruct-Python-bnb-4bit to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for xtremecoder/Qwen2.5-Coder-7B-Instruct-Python-bnb-4bit to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for xtremecoder/Qwen2.5-Coder-7B-Instruct-Python-bnb-4bit to start chatting
Load model with FastModel
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="xtremecoder/Qwen2.5-Coder-7B-Instruct-Python-bnb-4bit",
    max_seq_length=2048,
)
Quick Links

Qwen2.5 Coder Python Fine-Tuned Model

  • Developed by: xtremecoder
  • License: apache-2.0
  • Finetuned from model : unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit

Description

Fine-tuned the Qwen2.5 Coder 7B model for python code output.

From testing, the main difference is that the fine-tuned model directly generates code as output without additional text explanations and "fluff". The generated code itself is also different from the base model, sometimes more efficient than the original, but code quality doesn't always look to be as good as the original -- likely a function of limitated training datasets.

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Dataset used to train xtremecoder/Qwen2.5-Coder-7B-Instruct-Python-bnb-4bit