Instructions to use nightpartycoderteam/granite-4-nano-fix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nightpartycoderteam/granite-4-nano-fix with Transformers:

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

pipe = pipeline("text-generation", model="nightpartycoderteam/granite-4-nano-fix")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("nightpartycoderteam/granite-4-nano-fix")
model = AutoModelForCausalLM.from_pretrained("nightpartycoderteam/granite-4-nano-fix", device_map="auto")
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 nightpartycoderteam/granite-4-nano-fix with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nightpartycoderteam/granite-4-nano-fix"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nightpartycoderteam/granite-4-nano-fix",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/nightpartycoderteam/granite-4-nano-fix

SGLang

How to use nightpartycoderteam/granite-4-nano-fix 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 "nightpartycoderteam/granite-4-nano-fix" \
    --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": "nightpartycoderteam/granite-4-nano-fix",
		"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 "nightpartycoderteam/granite-4-nano-fix" \
        --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": "nightpartycoderteam/granite-4-nano-fix",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use nightpartycoderteam/granite-4-nano-fix with Docker Model Runner:
```
docker model run hf.co/nightpartycoderteam/granite-4-nano-fix
```

Model Card for granite-4-nano-fix

This model is a fine-tuned version of ibm-granite/granite-4.0-350m. It has been trained using TRL.

This model is trained for generating Financial Information eXchange (FIX) Protocol. It generates directly FIX messages and trained upon for this FIX structured data.

Quick start

Will be updated soon!

Training procedure

This model was trained with SFT.

Framework versions

TRL: 0.24.0
Transformers: 4.57.3
Pytorch: 2.9.1
Datasets: 4.3.0
Tokenizers: 0.22.1

Citations

Cite TRL as:

@misc{vonwerra2022trl,
    title        = {{TRL: Transformer Reinforcement Learning}},
    author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
    year         = 2020,
    journal      = {GitHub repository},
    publisher    = {GitHub},
    howpublished = {\url{https://github.com/huggingface/trl}}
}

Downloads last month: 11

Safetensors

Model size

0.4B params

Tensor type

BF16

Model tree for nightpartycoderteam/granite-4-nano-fix

Base model

ibm-granite/granite-4.0-350m-base

Finetuned

ibm-granite/granite-4.0-350m

Finetuned

(19)

this model