Instructions to use Flexan/1kz-bigcodemax-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Flexan/1kz-bigcodemax-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Flexan/1kz-bigcodemax-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Flexan/1kz-bigcodemax-GGUF", dtype="auto")

llama-cpp-python

How to use Flexan/1kz-bigcodemax-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Flexan/1kz-bigcodemax-GGUF",
	filename="bigcodemax.IQ3_M.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 Flexan/1kz-bigcodemax-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Flexan/1kz-bigcodemax-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Flexan/1kz-bigcodemax-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 Flexan/1kz-bigcodemax-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Flexan/1kz-bigcodemax-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 Flexan/1kz-bigcodemax-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Flexan/1kz-bigcodemax-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 Flexan/1kz-bigcodemax-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Flexan/1kz-bigcodemax-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Flexan/1kz-bigcodemax-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use Flexan/1kz-bigcodemax-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Flexan/1kz-bigcodemax-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": "Flexan/1kz-bigcodemax-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Flexan/1kz-bigcodemax-GGUF:Q4_K_M

SGLang

How to use Flexan/1kz-bigcodemax-GGUF 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 "Flexan/1kz-bigcodemax-GGUF" \
    --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": "Flexan/1kz-bigcodemax-GGUF",
		"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 "Flexan/1kz-bigcodemax-GGUF" \
        --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": "Flexan/1kz-bigcodemax-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use Flexan/1kz-bigcodemax-GGUF with Ollama:
```
ollama run hf.co/Flexan/1kz-bigcodemax-GGUF:Q4_K_M
```

Unsloth Studio new

How to use Flexan/1kz-bigcodemax-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 Flexan/1kz-bigcodemax-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 Flexan/1kz-bigcodemax-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Flexan/1kz-bigcodemax-GGUF to start chatting

Docker Model Runner
How to use Flexan/1kz-bigcodemax-GGUF with Docker Model Runner:
```
docker model run hf.co/Flexan/1kz-bigcodemax-GGUF:Q4_K_M
```

Lemonade

How to use Flexan/1kz-bigcodemax-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Flexan/1kz-bigcodemax-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.1kz-bigcodemax-GGUF-Q4_K_M

List all available models

lemonade list

GGUF Files for bigcodemax

These are the GGUF files for 1kz/bigcodemax.

Downloads

GGUF Link	Quantization	Description
Download	Q2_K	Lowest quality
Download	Q3_K_S
Download	IQ3_S	Integer quant, preferable over Q3_K_S
Download	IQ3_M	Integer quant
Download	Q3_K_M
Download	Q3_K_L
Download	IQ4_XS	Integer quant
Download	Q4_K_S	Fast with good performance
Download	Q4_K_M	Recommended: Perfect mix of speed and performance
Download	Q5_K_S
Download	Q5_K_M
Download	Q6_K	Very good quality
Download	Q8_0	Best quality
Download	f16	Full precision, don't bother; use a quant

Note from Flexan

I provide GGUFs and quantizations of publicly available models that do not have a GGUF equivalent available yet, usually for models I deem interesting and wish to try out.

If there are some quants missing that you'd like me to add, you may request one in the community tab. If you want to request a public model to be converted, you can also request that in the community tab. If you have questions regarding this model, please refer to the original model repo.

You can find more info about me and what I do here.

bigcodemax

Maximum coding + reasoning power in 8B parameters
Created by 1kz

An 8B model that punches way above its weight in code generation, software engineering, advanced reasoning, math, and long-context understanding.

Model Details

Developer: 1kz
Parameters: 8.0B (dense)
Context length: 128K (RoPE scaled)
Architecture: Llama-3.1 style (same tokenizer & chat template as Meta-Llama-3.1-8B-Instruct)
Base model: Fine-tuned from a strong 8B checkpoint
Training inspiration: Huge thanks to lfm for the incredible training recipes, data curation, synthetic data pipelines, and open methodology that made this model possible. Your work continues to inspire and push the frontier for compact high-performance models! ❤️

Strengths

Best-in-class code generation, editing, and debugging
Strong mathematical & logical reasoning (CoT & ToT)
Excellent at understanding and refactoring large codebases
Agentic coding, tool use, and multi-step problem solving
Fast inference on consumer hardware (single 4090 / 24GB VRAM)

Quick Start

from transformers import pipeline

pipe = pipeline(
    "text-generation",
    model="1kz/bigcodemax",
    device_map="auto",
    torch_dtype="auto"
)

messages = [
    {"role": "system", "content": "You are bigcodemax, an expert coding and reasoning assistant."},
    {"role": "user", "content": "Implement a thread-safe LRU Cache in Python with O(1) operations and explain every design choice step-by-step."}
]

output = pipe(messages, max_new_tokens=2048, temperature=0.6, top_p=0.95, do_sample=True)
print(output[0]["generated_text"][-1]["content"])
Benchmarks (internal eval)



Massive thank you to lfm — without your public training logs, data mixing strategies, and relentless open-source experimentation, a model this capable at only 8B would not exist. You're building the future of accessible frontier intelligence. 🚀

Downloads last month: 15

GGUF

Model size

7B params

Architecture

olmo2

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Model tree for Flexan/1kz-bigcodemax-GGUF

Base model

1kz/bigcodemax

Quantized

(1)

this model

Collection including Flexan/1kz-bigcodemax-GGUF

Community GGUFs

Collection

This collection contains quantized GGUF files for community models that did not have GGUF equivalents available yet. I do not own these models. • 58 items • Updated 30 days ago