Instructions to use Monibee-Fudgekins/gemma-coder-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Monibee-Fudgekins/gemma-coder-dev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Monibee-Fudgekins/gemma-coder-dev")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Monibee-Fudgekins/gemma-coder-dev", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Monibee-Fudgekins/gemma-coder-dev with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Monibee-Fudgekins/gemma-coder-dev" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Monibee-Fudgekins/gemma-coder-dev", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Monibee-Fudgekins/gemma-coder-dev
- SGLang
How to use Monibee-Fudgekins/gemma-coder-dev with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Monibee-Fudgekins/gemma-coder-dev" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Monibee-Fudgekins/gemma-coder-dev", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Monibee-Fudgekins/gemma-coder-dev" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Monibee-Fudgekins/gemma-coder-dev", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Unsloth Studio
How to use Monibee-Fudgekins/gemma-coder-dev with 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 Monibee-Fudgekins/gemma-coder-dev 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 Monibee-Fudgekins/gemma-coder-dev to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Monibee-Fudgekins/gemma-coder-dev to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Monibee-Fudgekins/gemma-coder-dev", max_seq_length=2048, ) - Docker Model Runner
How to use Monibee-Fudgekins/gemma-coder-dev with Docker Model Runner:
docker model run hf.co/Monibee-Fudgekins/gemma-coder-dev
Update model card (smoke run, pass@1 0.00%)
Browse files
README.md
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license: gemma
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base_model: unsloth/gemma-2-9b-it-bnb-4bit
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datasets:
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- sahil2801/CodeAlpaca-20k
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- code
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- coding-assistant
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model-index:
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- name: gemma-coder-dev
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---
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# gemma-coder-dev
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Coding-focused fine-tune of [`unsloth/gemma-2-9b-it-bnb-4bit`](https://huggingface.co/unsloth/gemma-2-9b-it-bnb-4bit),
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produced automatically by the weekly retrain pipeline in
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[remote-agent-dev-platform](https://github.com/Monibee-Fudgekins/remote-agent-dev-platform). **Last updated: 2026-06-16 17:
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promoted: **False**.
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## Model description
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license: gemma
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base_model: unsloth/gemma-2-9b-it-bnb-4bit
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datasets:
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- sahil2801/CodeAlpaca-20k
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- code
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- coding-assistant
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- qlora
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- unsloth
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model-index:
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- name: gemma-coder-dev
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results:
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- task:
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type: text-generation
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name: Code generation
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dataset:
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type: code-eval
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name: remote-agent-dev-platform coding_eval
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metrics:
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- type: pass@1
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value: 0.0000
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name: pass@1 (Python/JS/React/Go/Java/Swift)
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---
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# gemma-coder-dev
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Coding-focused fine-tune of [`unsloth/gemma-2-9b-it-bnb-4bit`](https://huggingface.co/unsloth/gemma-2-9b-it-bnb-4bit),
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produced automatically by the weekly retrain pipeline in
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[remote-agent-dev-platform](https://github.com/Monibee-Fudgekins/remote-agent-dev-platform). **Last updated: 2026-06-16 17:51 UTC** 路 run mode: `smoke` 路
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promoted: **False**.
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## Model description
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