Instructions to use ZeroWw/Seed-Coder-8B-Reasoning-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ZeroWw/Seed-Coder-8B-Reasoning-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="ZeroWw/Seed-Coder-8B-Reasoning-GGUF",
	filename="Seed-Coder-8B-Reasoning.f16.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 ZeroWw/Seed-Coder-8B-Reasoning-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ZeroWw/Seed-Coder-8B-Reasoning-GGUF:F16
# Run inference directly in the terminal:
llama-cli -hf ZeroWw/Seed-Coder-8B-Reasoning-GGUF:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ZeroWw/Seed-Coder-8B-Reasoning-GGUF:F16
# Run inference directly in the terminal:
llama-cli -hf ZeroWw/Seed-Coder-8B-Reasoning-GGUF:F16

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 ZeroWw/Seed-Coder-8B-Reasoning-GGUF:F16
# Run inference directly in the terminal:
./llama-cli -hf ZeroWw/Seed-Coder-8B-Reasoning-GGUF:F16

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 ZeroWw/Seed-Coder-8B-Reasoning-GGUF:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ZeroWw/Seed-Coder-8B-Reasoning-GGUF:F16

Use Docker

docker model run hf.co/ZeroWw/Seed-Coder-8B-Reasoning-GGUF:F16

LM Studio
Jan

vLLM

How to use ZeroWw/Seed-Coder-8B-Reasoning-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ZeroWw/Seed-Coder-8B-Reasoning-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": "ZeroWw/Seed-Coder-8B-Reasoning-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ZeroWw/Seed-Coder-8B-Reasoning-GGUF:F16

Ollama
How to use ZeroWw/Seed-Coder-8B-Reasoning-GGUF with Ollama:
```
ollama run hf.co/ZeroWw/Seed-Coder-8B-Reasoning-GGUF:F16
```

Unsloth Studio new

How to use ZeroWw/Seed-Coder-8B-Reasoning-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 ZeroWw/Seed-Coder-8B-Reasoning-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 ZeroWw/Seed-Coder-8B-Reasoning-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ZeroWw/Seed-Coder-8B-Reasoning-GGUF to start chatting

Docker Model Runner
How to use ZeroWw/Seed-Coder-8B-Reasoning-GGUF with Docker Model Runner:
```
docker model run hf.co/ZeroWw/Seed-Coder-8B-Reasoning-GGUF:F16
```

Lemonade

How to use ZeroWw/Seed-Coder-8B-Reasoning-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ZeroWw/Seed-Coder-8B-Reasoning-GGUF:F16

Run and chat with the model

lemonade run user.Seed-Coder-8B-Reasoning-GGUF-F16

List all available models

lemonade list

ZeroWw commited on May 12, 2025

Commit

e664151

verified ·

1 Parent(s): 90dd53b

Upload folder using huggingface_hub

Browse files

Files changed (8) hide show

.gitattributes +6 -0
README.md +17 -0
Seed-Coder-8B-Reasoning.f16.gguf +3 -0
Seed-Coder-8B-Reasoning.q5_k.gguf +3 -0
Seed-Coder-8B-Reasoning.q6_k.gguf +3 -0
Seed-Coder-8B-Reasoning.q8_0.gguf +3 -0
Seed-Coder-8B-Reasoning.q8_p.gguf +3 -0
Seed-Coder-8B-Reasoning.q8q4.gguf +3 -0

.gitattributes CHANGED Viewed

@@ -33,3 +33,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text

 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
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README.md ADDED Viewed

	@@ -0,0 +1,17 @@

+---
+license: mit
+language:
+- en
+pipeline_tag: text-generation
+---
+My own (ZeroWw) quantizations.
+output and embed tensors quantized to f16.
+all other tensors quantized to q5_k or q6_k.
+Result:
+both f16.q6 and f16.q5 are smaller than q8_0 standard quantization
+and they perform as well as the pure f16.
+Updated on: Mon May 12, 11:36:29

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