Instructions to use minosu/godot_dodo_4x_60k_starcoder_15b_2ep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use minosu/godot_dodo_4x_60k_starcoder_15b_2ep with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="minosu/godot_dodo_4x_60k_starcoder_15b_2ep")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("minosu/godot_dodo_4x_60k_starcoder_15b_2ep")
model = AutoModelForCausalLM.from_pretrained("minosu/godot_dodo_4x_60k_starcoder_15b_2ep")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use minosu/godot_dodo_4x_60k_starcoder_15b_2ep with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "minosu/godot_dodo_4x_60k_starcoder_15b_2ep"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "minosu/godot_dodo_4x_60k_starcoder_15b_2ep",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/minosu/godot_dodo_4x_60k_starcoder_15b_2ep

SGLang

How to use minosu/godot_dodo_4x_60k_starcoder_15b_2ep 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 "minosu/godot_dodo_4x_60k_starcoder_15b_2ep" \
    --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": "minosu/godot_dodo_4x_60k_starcoder_15b_2ep",
		"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 "minosu/godot_dodo_4x_60k_starcoder_15b_2ep" \
        --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": "minosu/godot_dodo_4x_60k_starcoder_15b_2ep",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use minosu/godot_dodo_4x_60k_starcoder_15b_2ep with Docker Model Runner:
```
docker model run hf.co/minosu/godot_dodo_4x_60k_starcoder_15b_2ep
```

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Check out the documentation for more information.

godot_dodo_4x_60k_starcoder_15b_2ep

Model details

Trained in May 2023.

Godot-Dodo models are instruction-following models finetuned from open-source base models.

Please refer to the README of the GitHub repository for detailed information.

Evaluation datasets

The model was evaluated using code instruction prompts. More details in the GitHub repository.

Training dataset

The model was trained on a 60k rows instruction following dataset, which is released in the Github repository.

Training parameters

For exact parameters used, please refer to this page in the GitHub repository.

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