Instructions to use snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF", filename="Seed-Coder-8B-Instruct.Q4_K_M.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-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 snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-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 snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF:Q4_K_M
Use Docker
docker model run hf.co/snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF with Ollama:
ollama run hf.co/snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF:Q4_K_M
- Unsloth Studio
How to use snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-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 snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-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 snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF with Docker Model Runner:
docker model run hf.co/snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF:Q4_K_M
- Lemonade
How to use snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Seed-Coder-8B-Instruct-Rust-Strandset-GGUF-Q4_K_M
List all available models
lemonade list
Upload README.md with huggingface_hub
Browse files
README.md
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---
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license: apache-2.0
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base_model: ByteDance-Seed/Seed-Coder-8B-Instruct
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tags:
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- gguf
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- llama.cpp
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- seed-coder
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- rust
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- strandset
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- code
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- q4_k_m
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- q6_k
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---
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# Seed-Coder-8B-Instruct Rust Strandset GGUF
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GGUF export of a Seed-Coder-8B-Instruct LoRA trained on a 20k-row subset of `Fortytwo-Network/Strandset-Rust-v1`.
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Base model:
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`ByteDance-Seed/Seed-Coder-8B-Instruct`
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LoRA adapter:
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`snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-LoRA`
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Dataset:
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`Fortytwo-Network/Strandset-Rust-v1`
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Mapping used:
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- `input_data` → user
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- `output_data` → assistant
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- `task_category` → system
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- `crate_name` → system
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- `test` → none
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Training config:
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- Method: LoRA
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- Context: 4096
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- Epochs: 1
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- LR: 2e-4
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- Rank: 16
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- Alpha: 32
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- Dropout: 0.0
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- Batch size: 16
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- Grad accum: 2
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- Effective batch: 32
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- Weight decay: 0.001
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- Warmup steps: 25
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- Packing: off
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- Train on completions: on
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Files:
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- `Seed-Coder-8B-Instruct.Q4_K_M.gguf`
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- `Seed-Coder-8B-Instruct.Q6_K.gguf`
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Note: this model was trained on Strandset-style structured Rust code tasks. It may emit JSON-style wrappers such as `{"code": "..."}` depending on prompting.
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## llama.cpp
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```bash
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llama-cli \
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-m Seed-Coder-8B-Instruct.Q4_K_M.gguf \
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--jinja \
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--single-turn \
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--temp 0.1 \
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--top-p 0.8 \
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--repeat-penalty 1.05 \
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-p "Write only Rust code. No markdown. Implement parse_duration(s: &str) -> Result<std::time::Duration, String> supporting 10s, 5m, 2h. Include tests."
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