Instructions to use dphn/dolphincoder-starcoder2-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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
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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/).
[](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/) |