Instructions to use dphn/dolphincoder-starcoder2-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use dphn/dolphincoder-starcoder2-7b with Transformers:

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

pipe = pipeline("text-generation", model="dphn/dolphincoder-starcoder2-7b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("dphn/dolphincoder-starcoder2-7b")
model = AutoModelForCausalLM.from_pretrained("dphn/dolphincoder-starcoder2-7b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use dphn/dolphincoder-starcoder2-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "dphn/dolphincoder-starcoder2-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "dphn/dolphincoder-starcoder2-7b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/dphn/dolphincoder-starcoder2-7b

SGLang

How to use dphn/dolphincoder-starcoder2-7b 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 "dphn/dolphincoder-starcoder2-7b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "dphn/dolphincoder-starcoder2-7b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "dphn/dolphincoder-starcoder2-7b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "dphn/dolphincoder-starcoder2-7b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use dphn/dolphincoder-starcoder2-7b with Docker Model Runner:
```
docker model run hf.co/dphn/dolphincoder-starcoder2-7b
```

dolphincoder-starcoder2-7b / README.md

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	---
	datasets:
	- cognitivecomputations/dolphin
	- jondurbin/airoboros-2.2.1
	- cognitivecomputations/dolphin-coder
	- teknium/openhermes
	- ise-uiuc/Magicoder-OSS-Instruct-75K
	- ise-uiuc/Magicoder-Evol-Instruct-110K
	- m-a-p/Code-Feedback
	- m-a-p/CodeFeedback-Filtered-Instruction
	- microsoft/orca-math-word-problems-200k
	language:
	- en
	license: bigcode-openrail-m
	---

	DolphinCoder StarCoder2 7b 🐬

	sponsored by [latitude.sh](https://www.latitude.sh/).

	[![Discord](https://img.shields.io/discord/1156064224225808488?logo=Discord&logoColor=%23ffffff&label=Discord&link=https%3A%2F%2Fdiscord.gg%2FtCMkMDDHwm)](https://discord.gg/cognitivecomputations)
	Discord: https://discord.gg/cognitivecomputations

	<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" />

	This model is based on StarCoder2-7b and is subject to bigcode-openrail-m license.

	This Dolphin is really good at coding, I trained with a lot of coding data.

	This model is uncensored. I have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant to any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models
	You are responsible for any content you create using this model. Enjoy responsibly.

	## Training
	It took 2 days to train 3 epochs on 8x L40S's using qLoRA and Axolotl

	Prompt format:
	This model uses ChatML prompt format.
	```
	<\|im_start\|>system
	You are DolphinCoder, a helpful AI programming assistant.<\|im_end\|>
	<\|im_start\|>user
	{prompt}<\|im_end\|>
	<\|im_start\|>assistant

	```

	Example:
	```
	<\|im_start\|>system
	You are DolphinCoder, a master at software engineering and coding in any programming language.
	<\|im_start\|>user
	Please write me a program in golang that parses all the lines in a file, and reverses them character-wise, and saves it to a new file.
	<\|im_start\|>assistant
	```

	## Quantized models

	- [dagbs/-GGUF](https://huggingface.co/dagbs/dolphincoder-starcoder2-7b-GGUF)

	## Gratitude
	- This model was made possible by the generous sponsorship of [latitude.sh](https://www.latitude.sh/).
	- Welcome Microsoft to Open Source AI! Thank you for the Orca-Math Dataset!
	- Huge thank you to [BigCode](https://www.bigcode-project.org/) for training and publishing the weights of StarCoder2
	- HUGE Thank you to the dataset authors: @ise-uiuc, @teknium, @m-a-p
	- And HUGE thanks to @winglian and the Axolotl contributors for making the best training framework!
	- [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
	- Thank you to all the other people in the Open Source AI community who have taught me and helped me along the way.

	## Example Output


	[If you would like to financially support my efforts](https://ko-fi.com/erichartford)

	[swag](https://fa7113.myshopify.com/)