Instructions to use Bifrost-AI/NextCoder-Mirage-sol-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Bifrost-AI/NextCoder-Mirage-sol-7B with Transformers:

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

pipe = pipeline("text-generation", model="Bifrost-AI/NextCoder-Mirage-sol-7B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Bifrost-AI/NextCoder-Mirage-sol-7B")
model = AutoModelForCausalLM.from_pretrained("Bifrost-AI/NextCoder-Mirage-sol-7B")
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

vLLM

How to use Bifrost-AI/NextCoder-Mirage-sol-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Bifrost-AI/NextCoder-Mirage-sol-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Bifrost-AI/NextCoder-Mirage-sol-7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Bifrost-AI/NextCoder-Mirage-sol-7B

SGLang

How to use Bifrost-AI/NextCoder-Mirage-sol-7B 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 "Bifrost-AI/NextCoder-Mirage-sol-7B" \
    --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": "Bifrost-AI/NextCoder-Mirage-sol-7B",
		"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 "Bifrost-AI/NextCoder-Mirage-sol-7B" \
        --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": "Bifrost-AI/NextCoder-Mirage-sol-7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Bifrost-AI/NextCoder-Mirage-sol-7B with Docker Model Runner:
```
docker model run hf.co/Bifrost-AI/NextCoder-Mirage-sol-7B
```

BifrostTitan commited on Jul 14, 2025

Commit

044c794

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1 Parent(s): 6a54c0c

Update README.md

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@@ -42,6 +42,3 @@ NextCoder Mirage SOL 7B is in active development with additional fine-tuning ses
 - **Planned Extensions:**
   - **C# (Solnet):** To be integrated later for .NET ecosystem coverage.
-## Disclaimer
-We do not recommend using Qwen3 Bifrost SOL 4B in commercial or real-world applications without further testing and development. This current model(v1) is intended for research and development purposes. While efforts have been made to align it using SFT and DPO, it may still produce outputs that are unexpected, biased, or inaccurate. Please use responsibly.


42	- Planned Extensions:
43	- C# (Solnet): To be integrated later for .NET ecosystem coverage.
44