Instructions to use bartowski/dolphincoder-starcoder2-7b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use bartowski/dolphincoder-starcoder2-7b-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="bartowski/dolphincoder-starcoder2-7b-GGUF", filename="dolphincoder-starcoder2-7b-Q2_K.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use bartowski/dolphincoder-starcoder2-7b-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf bartowski/dolphincoder-starcoder2-7b-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf bartowski/dolphincoder-starcoder2-7b-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf bartowski/dolphincoder-starcoder2-7b-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf bartowski/dolphincoder-starcoder2-7b-GGUF:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf bartowski/dolphincoder-starcoder2-7b-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf bartowski/dolphincoder-starcoder2-7b-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf bartowski/dolphincoder-starcoder2-7b-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf bartowski/dolphincoder-starcoder2-7b-GGUF:Q4_K_M
Use Docker
docker model run hf.co/bartowski/dolphincoder-starcoder2-7b-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use bartowski/dolphincoder-starcoder2-7b-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bartowski/dolphincoder-starcoder2-7b-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bartowski/dolphincoder-starcoder2-7b-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/bartowski/dolphincoder-starcoder2-7b-GGUF:Q4_K_M
- Ollama
How to use bartowski/dolphincoder-starcoder2-7b-GGUF with Ollama:
ollama run hf.co/bartowski/dolphincoder-starcoder2-7b-GGUF:Q4_K_M
- Unsloth Studio
How to use bartowski/dolphincoder-starcoder2-7b-GGUF 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 bartowski/dolphincoder-starcoder2-7b-GGUF 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 bartowski/dolphincoder-starcoder2-7b-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for bartowski/dolphincoder-starcoder2-7b-GGUF to start chatting
- Docker Model Runner
How to use bartowski/dolphincoder-starcoder2-7b-GGUF with Docker Model Runner:
docker model run hf.co/bartowski/dolphincoder-starcoder2-7b-GGUF:Q4_K_M
- Lemonade
How to use bartowski/dolphincoder-starcoder2-7b-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bartowski/dolphincoder-starcoder2-7b-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.dolphincoder-starcoder2-7b-GGUF-Q4_K_M
List all available models
lemonade list
Llamacpp quants
Browse files- .gitattributes +12 -0
- README.md +42 -0
- dolphincoder-starcoder2-7b-Q2_K.gguf +3 -0
- dolphincoder-starcoder2-7b-Q3_K_L.gguf +3 -0
- dolphincoder-starcoder2-7b-Q3_K_M.gguf +3 -0
- dolphincoder-starcoder2-7b-Q3_K_S.gguf +3 -0
- dolphincoder-starcoder2-7b-Q4_0.gguf +3 -0
- dolphincoder-starcoder2-7b-Q4_K_M.gguf +3 -0
- dolphincoder-starcoder2-7b-Q4_K_S.gguf +3 -0
- dolphincoder-starcoder2-7b-Q5_0.gguf +3 -0
- dolphincoder-starcoder2-7b-Q5_K_M.gguf +3 -0
- dolphincoder-starcoder2-7b-Q5_K_S.gguf +3 -0
- dolphincoder-starcoder2-7b-Q6_K.gguf +3 -0
- dolphincoder-starcoder2-7b-Q8_0.gguf +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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dolphincoder-starcoder2-7b-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
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dolphincoder-starcoder2-7b-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
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dolphincoder-starcoder2-7b-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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dolphincoder-starcoder2-7b-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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dolphincoder-starcoder2-7b-Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
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dolphincoder-starcoder2-7b-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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dolphincoder-starcoder2-7b-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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dolphincoder-starcoder2-7b-Q5_0.gguf filter=lfs diff=lfs merge=lfs -text
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dolphincoder-starcoder2-7b-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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datasets:
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- cognitivecomputations/dolphin
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- jondurbin/airoboros-2.2.1
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- cognitivecomputations/dolphin-coder
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- teknium/openhermes
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- ise-uiuc/Magicoder-OSS-Instruct-75K
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- ise-uiuc/Magicoder-Evol-Instruct-110K
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- m-a-p/Code-Feedback
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- m-a-p/CodeFeedback-Filtered-Instruction
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- microsoft/orca-math-word-problems-200k
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language:
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- en
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license: bigcode-openrail-m
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quantized_by: bartowski
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pipeline_tag: text-generation
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---
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## Llamacpp Quantizations of dolphincoder-starcoder2-7b
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Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2354">b2354</a> for quantization.
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Original model: https://huggingface.co/cognitivecomputations/dolphincoder-starcoder2-7b
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Download a file (not the whole branch) from below:
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| Filename | Quant type | File Size | Description |
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| -------- | ---------- | --------- | ----------- |
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| [dolphincoder-starcoder2-7b-Q8_0.gguf](https://huggingface.co/bartowski/dolphincoder-starcoder2-7b-GGUF//main/dolphincoder-starcoder2-7b-Q8_0.gguf) | Q8_0 | 7.86GB | Extremely high quality, generally unneeded but max available quant. |
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| [dolphincoder-starcoder2-7b-Q6_K.gguf](https://huggingface.co/bartowski/dolphincoder-starcoder2-7b-GGUF//main/dolphincoder-starcoder2-7b-Q6_K.gguf) | Q6_K | 6.07GB | Very high quality, near perfect, *recommended*. |
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| [dolphincoder-starcoder2-7b-Q5_K_M.gguf](https://huggingface.co/bartowski/dolphincoder-starcoder2-7b-GGUF//main/dolphincoder-starcoder2-7b-Q5_K_M.gguf) | Q5_K_M | 5.31GB | High quality, very usable. |
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| [dolphincoder-starcoder2-7b-Q5_K_S.gguf](https://huggingface.co/bartowski/dolphincoder-starcoder2-7b-GGUF//main/dolphincoder-starcoder2-7b-Q5_K_S.gguf) | Q5_K_S | 5.12GB | High quality, very usable. |
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| [dolphincoder-starcoder2-7b-Q5_0.gguf](https://huggingface.co/bartowski/dolphincoder-starcoder2-7b-GGUF//main/dolphincoder-starcoder2-7b-Q5_0.gguf) | Q5_0 | 5.12GB | High quality, older format, generally not recommended. |
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| [dolphincoder-starcoder2-7b-Q4_K_M.gguf](https://huggingface.co/bartowski/dolphincoder-starcoder2-7b-GGUF//main/dolphincoder-starcoder2-7b-Q4_K_M.gguf) | Q4_K_M | 4.58GB | Good quality, similar to 4.25 bpw. |
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| [dolphincoder-starcoder2-7b-Q4_K_S.gguf](https://huggingface.co/bartowski/dolphincoder-starcoder2-7b-GGUF//main/dolphincoder-starcoder2-7b-Q4_K_S.gguf) | Q4_K_S | 4.31GB | Slightly lower quality with small space savings. |
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| [dolphincoder-starcoder2-7b-Q4_0.gguf](https://huggingface.co/bartowski/dolphincoder-starcoder2-7b-GGUF//main/dolphincoder-starcoder2-7b-Q4_0.gguf) | Q4_0 | 4.22GB | Decent quality, older format, generally not recommended. |
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| [dolphincoder-starcoder2-7b-Q3_K_L.gguf](https://huggingface.co/bartowski/dolphincoder-starcoder2-7b-GGUF//main/dolphincoder-starcoder2-7b-Q3_K_L.gguf) | Q3_K_L | 4.17GB | Lower quality but usable, good for low RAM availability. |
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| [dolphincoder-starcoder2-7b-Q3_K_M.gguf](https://huggingface.co/bartowski/dolphincoder-starcoder2-7b-GGUF//main/dolphincoder-starcoder2-7b-Q3_K_M.gguf) | Q3_K_M | 3.78GB | Even lower quality. |
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| [dolphincoder-starcoder2-7b-Q3_K_S.gguf](https://huggingface.co/bartowski/dolphincoder-starcoder2-7b-GGUF//main/dolphincoder-starcoder2-7b-Q3_K_S.gguf) | Q3_K_S | 3.27GB | Low quality, not recommended. |
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| [dolphincoder-starcoder2-7b-Q2_K.gguf](https://huggingface.co/bartowski/dolphincoder-starcoder2-7b-GGUF//main/dolphincoder-starcoder2-7b-Q2_K.gguf) | Q2_K | 2.91GB | Extremely low quality, *not* recommended.
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Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski
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