Instructions to use nassimjp/ipashtoCoder-9B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use nassimjp/ipashtoCoder-9B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="nassimjp/ipashtoCoder-9B-GGUF", filename="omnicoder-9b-bf16.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use nassimjp/ipashtoCoder-9B-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf nassimjp/ipashtoCoder-9B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf nassimjp/ipashtoCoder-9B-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 nassimjp/ipashtoCoder-9B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf nassimjp/ipashtoCoder-9B-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 nassimjp/ipashtoCoder-9B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf nassimjp/ipashtoCoder-9B-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 nassimjp/ipashtoCoder-9B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf nassimjp/ipashtoCoder-9B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/nassimjp/ipashtoCoder-9B-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use nassimjp/ipashtoCoder-9B-GGUF with Ollama:
ollama run hf.co/nassimjp/ipashtoCoder-9B-GGUF:Q4_K_M
- Unsloth Studio new
How to use nassimjp/ipashtoCoder-9B-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 nassimjp/ipashtoCoder-9B-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 nassimjp/ipashtoCoder-9B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for nassimjp/ipashtoCoder-9B-GGUF to start chatting
- Pi new
How to use nassimjp/ipashtoCoder-9B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf nassimjp/ipashtoCoder-9B-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "nassimjp/ipashtoCoder-9B-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use nassimjp/ipashtoCoder-9B-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf nassimjp/ipashtoCoder-9B-GGUF:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default nassimjp/ipashtoCoder-9B-GGUF:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use nassimjp/ipashtoCoder-9B-GGUF with Docker Model Runner:
docker model run hf.co/nassimjp/ipashtoCoder-9B-GGUF:Q4_K_M
- Lemonade
How to use nassimjp/ipashtoCoder-9B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull nassimjp/ipashtoCoder-9B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.ipashtoCoder-9B-GGUF-Q4_K_M
List all available models
lemonade list
Duplicate from Tesslate/OmniCoder-9B-GGUF
Browse filesCo-authored-by: Manav Majumdar <smirki@users.noreply.huggingface.co>
- .gitattributes +48 -0
- README.md +67 -0
- omnicoder-9b-bf16.gguf +3 -0
- omnicoder-9b-q2_k.gguf +3 -0
- omnicoder-9b-q3_k_l.gguf +3 -0
- omnicoder-9b-q3_k_m.gguf +3 -0
- omnicoder-9b-q3_k_s.gguf +3 -0
- omnicoder-9b-q4_0.gguf +3 -0
- omnicoder-9b-q4_k_m.gguf +3 -0
- omnicoder-9b-q4_k_s.gguf +3 -0
- omnicoder-9b-q5_0.gguf +3 -0
- omnicoder-9b-q5_k_m.gguf +3 -0
- omnicoder-9b-q5_k_s.gguf +3 -0
- omnicoder-9b-q6_k.gguf +3 -0
- omnicoder-9b-q8_0.gguf +3 -0
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---
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base_model: Tesslate/OmniCoder-9B
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tags:
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- llama-cpp
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- gguf
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- qwen3.5
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- omnicoder
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- tesslate
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- code
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- agent
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license: apache-2.0
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---
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<div align="center">
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<img src="https://huggingface.co/Tesslate/OmniCoder-9B/resolve/main/omnicoder-banner.png" alt="OmniCoder" width="720">
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# OmniCoder-9B-GGUF
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### GGUF quantizations of [OmniCoder-9B](https://huggingface.co/Tesslate/OmniCoder-9B)
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[](https://opensource.org/licenses/Apache-2.0)
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[](https://huggingface.co/Tesslate/OmniCoder-9B)
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</div>
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---
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## Available Quantizations
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| Quantization | Size | Use Case |
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|:---|---:|:---|
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| `Q2_K` | ~3.8 GB | Extreme compression, lowest quality |
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| `Q3_K_S` | ~4.3 GB | Small footprint |
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| `Q3_K_M` | ~4.6 GB | Small footprint, balanced |
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| `Q3_K_L` | ~4.9 GB | Small footprint, higher quality |
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| `Q4_0` | ~5.3 GB | Good balance |
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| `Q4_K_S` | ~5.4 GB | Good balance |
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| **`Q4_K_M`** | **~5.7 GB** | **Recommended for most users** |
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| `Q5_0` | ~6.3 GB | High quality |
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| `Q5_K_S` | ~6.3 GB | High quality |
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| `Q5_K_M` | ~6.5 GB | High quality, balanced |
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| `Q6_K` | ~7.4 GB | Near-lossless |
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| `Q8_0` | ~9.5 GB | Highest quality quantization |
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| `BF16` | ~17.9 GB | Full precision |
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## Usage
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```bash
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# Install llama.cpp
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brew install llama.cpp # macOS
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# or build from source: https://github.com/ggml-org/llama.cpp
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# Interactive chat
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llama-cli --hf-repo Tesslate/OmniCoder-9B-GGUF --hf-file omnicoder-9b-q4_k_m.gguf -p "Your prompt" -c 8192
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# Server mode (OpenAI-compatible API)
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llama-server --hf-repo Tesslate/OmniCoder-9B-GGUF --hf-file omnicoder-9b-q4_k_m.gguf -c 8192
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```
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---
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<div align="center">
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**Built by [Tesslate](https://tesslate.com)** | See full model card: [OmniCoder-9B](https://huggingface.co/Tesslate/OmniCoder-9B)
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</div>
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omnicoder-9b-bf16.gguf
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size 17920696640
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version https://git-lfs.github.com/spec/v1
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omnicoder-9b-q6_k.gguf
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
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size 7359258944
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omnicoder-9b-q8_0.gguf
ADDED
|
@@ -0,0 +1,3 @@
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|
|
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|
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|
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| 1 |
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version https://git-lfs.github.com/spec/v1
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size 9527501120
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