Instructions to use Veri-Code/ReForm-SFT-0.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Veri-Code/ReForm-SFT-0.5B with Transformers:

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

pipe = pipeline("text-generation", model="Veri-Code/ReForm-SFT-0.5B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Veri-Code/ReForm-SFT-0.5B")
model = AutoModelForCausalLM.from_pretrained("Veri-Code/ReForm-SFT-0.5B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Veri-Code/ReForm-SFT-0.5B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Veri-Code/ReForm-SFT-0.5B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Veri-Code/ReForm-SFT-0.5B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Veri-Code/ReForm-SFT-0.5B

SGLang

How to use Veri-Code/ReForm-SFT-0.5B 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 "Veri-Code/ReForm-SFT-0.5B" \
    --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": "Veri-Code/ReForm-SFT-0.5B",
		"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 "Veri-Code/ReForm-SFT-0.5B" \
        --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": "Veri-Code/ReForm-SFT-0.5B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Veri-Code/ReForm-SFT-0.5B with Docker Model Runner:
```
docker model run hf.co/Veri-Code/ReForm-SFT-0.5B
```

Improve model card for Re:Form: add metadata, links, and usage example

by nielsr HF Staff - opened Jul 25, 2025

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+83

-3

nielsr

Jul 25, 2025

This PR significantly enhances the model card for the Re:Form model by:

Adding pipeline_tag: text-generation and library_name: transformers to the metadata, which improves discoverability and integration with the Hugging Face Hub features.
Including relevant tags such as code-generation, formal-verification, reinforcement-learning, and dafny for better categorization.
Providing a concise model description summarizing the paper's abstract.
Including the project page link (https://veri-code.github.io/ReForm-page) and updating the GitHub repository link to point to the main project repository (https://github.com/Veri-Code/Veri-Code).
Adding the overall pipeline image from the project's GitHub repository for visual context.
Providing a runnable Python code snippet to demonstrate basic usage with the transformers library for Dafny code generation.
Including the full BibTeX citation for proper academic attribution.
Removing the unnecessary "File information" section to keep the model card clean and focused.

These updates greatly improve the model's documentation and user experience on the Hugging Face Hub.

Improve model card for Re:Form: add metadata, links, and usage examplebcc16777

SiniShell1 changed pull request status to merged Jul 25, 2025

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