Instructions to use Monibee-Fudgekins/gemma-coder-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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
```

Monibee-Fudgekins commited on 8 days ago

Commit

93973d0

verified ·

1 Parent(s): b2d5724

Upload model trained with Unsloth

Browse files

Upload model trained with Unsloth 2x faster

Files changed (3) hide show

README.md +17 -17
adapter_config.json +1 -6
adapter_model.safetensors +2 -2

README.md CHANGED Viewed

@@ -2,27 +2,27 @@
 license: gemma
 base_model: google/gemma-4-26B-A4B-it
 datasets:
-  - sahil2801/CodeAlpaca-20k
 library_name: transformers
 pipeline_tag: text-generation
 tags:
-  - code
-  - coding-assistant
-  - qlora
-  - unsloth
 model-index:
-  - name: gemma-coder-dev
-    results:
-      - task:
-          type: text-generation
-          name: Code generation
-        dataset:
-          type: code-eval
-          name: remote-agent-dev-platform coding_eval
-        metrics:
-          - type: pass@1
-            value: 0.0000
-            name: pass@1 (Python/JS/React/Go/Java/Swift)
 ---
 # gemma-coder-dev

 license: gemma
 base_model: google/gemma-4-26B-A4B-it
 datasets:
+- sahil2801/CodeAlpaca-20k
 library_name: transformers
 pipeline_tag: text-generation
 tags:
+- code
+- coding-assistant
+- qlora
+- unsloth
 model-index:
+- name: gemma-coder-dev
+  results:
+  - task:
+      type: text-generation
+      name: Code generation
+    dataset:
+      name: remote-agent-dev-platform coding_eval
+      type: code-eval
+    metrics:
+    - type: pass@1
+      value: 0.0
+      name: pass@1 (Python/JS/React/Go/Java/Swift)
 ---
 # gemma-coder-dev

adapter_config.json CHANGED Viewed

@@ -32,12 +32,7 @@
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   "rank_pattern": {},
   "revision": null,
-  "target_modules": [
-    "o_proj",
-    "v_proj",
-    "q_proj",
-    "k_proj"
-  ],
   "target_parameters": null,
   "task_type": "CAUSAL_LM",
   "trainable_token_indices": null,

   "r": 16,
   "rank_pattern": {},
   "revision": null,
+  "target_modules": "(?:.*?(?:language|text).*?(?:self_attn|attention|attn|mixer).*?(?:q_proj|k_proj|v_proj|o_proj))|(?:\\bmodel\\.layers\\.[\\d]{1,}\\.(?:self_attn|attention|attn|mixer)\\.(?:(?:q_proj|k_proj|v_proj|o_proj)))",
   "target_parameters": null,
   "task_type": "CAUSAL_LM",
   "trainable_token_indices": null,

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