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StepFun-Formalizer-7B-GGUF
tinyopsec/StepFun-Formalizer-7B-GGUF
StepFun-Formalizer-7B-GGUF is a text generation model from tinyopsec. Use it when you need the model to write or continue text. It is set up for gguf. The card lists the license as apache-2.0.
GGUF quantizations of stepfun-ai/StepFun-Formalizer-7B.
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Repo size
15.2 GB
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Repo makeup
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.gguf15.2 GB · 100%
At a glance
- Task
- Text Generation
- Library
- gguf
- License
- apache-2.0
- Access
- Public
- Created
- Sep 16, 2026
- Updated
- Sep 16, 2026
- SHA
- 186a6457
Try a prompt
Base models
Model card
From the Hugging Face model README
StepFun-Formalizer-7B GGUF
GGUF quantizations of stepfun-ai/StepFun-Formalizer-7B.
About the Model
StepFun-Formalizer-7B is a large language model designed to translate natural-language mathematical problems into formal statements in Lean 4. It is fine-tuned on top of deepseek-ai/DeepSeek-R1-Distill-Qwen-7B and achieves state-of-the-art performance on autoformalization benchmarks including FormalMATH-Lite, ProverBench, and CombiBench.
Quantization Files
| File | Bits | Size | Use Case |
|---|---|---|---|
| model_f16.gguf | 16 | ~15 GB | Maximum quality, reference |
| model_q8_0.gguf | 8 | ~8.1 GB | Best quality, recommended if VRAM allows |
| model_q6_k.gguf | 6 | ~6.3 GB | Near-lossless, great balance |
| model_q5_k_m.gguf | 5 | ~5.5 GB | Recommended for most users |
| model_q5_k_s.gguf | 5 | ~5.3 GB | Slightly smaller than Q5_K_M |
| model_q4_k_m.gguf | 4 | ~4.7 GB | Good quality/size balance |
| model_q4_k_s.gguf | 4 | ~4.5 GB | Smaller Q4 variant |
| model_q3_k_l.gguf | 3 | ~3.9 GB | Low VRAM, acceptable quality |
| model_q3_k_m.gguf | 3 | ~3.6 GB | Lower VRAM |
| model_q3_k_s.gguf | 3 | ~3.3 GB | Minimal footprint |
| model_q2_k.gguf | 2 | ~2.8 GB | Smallest, significant quality loss |
VRAM Requirements
| Quantization | VRAM |
|---|---|
| F16 | ~16 GB |
| Q8_0 | ~9 GB |
| Q6_K | ~7 GB |
| Q5_K_M | ~6 GB |
| Q4_K_M | ~5 GB |
| Q3_K_M | ~4 GB |
| Q2_K | ~3.5 GB |
Usage
llama.cpp
./llama-cli -m model_q4_k_m.gguf -p "Please autoformalize the following problem: ..." -n 512
llama-cpp-python
from llama_cpp import Llama
llm = Llama(model_path="model_q4_k_m.gguf", n_ctx=4096)
output = llm("Please autoformalize the following problem: ...", max_tokens=512)
print(output["choices"][0]["text"])
LM Studio
Download the desired .gguf file and load it directly in LM Studio.
Ollama
ollama run hf.co/tinyopsec/StepFun-Formalizer-7B-GGUF:Q4_K_M
Prompt Format
<｜User｜>Please autoformalize the following problem:
<informal problem here>
<｜Assistant｜>
Links
- Original model: stepfun-ai/StepFun-Formalizer-7B
- Paper: arxiv.org/abs/2508.04440
- Code: github.com/stepfun-ai/StepFun-Formalizer
- Task
- Text Generation
- Library
- gguf
- License
- apache-2.0
- Languages
- en
- Created
- Sep 16, 2026
- Updated
- Sep 16, 2026