Instructions to use microsoft/FrogMini-14B-2510 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use microsoft/FrogMini-14B-2510 with Transformers:

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

pipe = pipeline("text-generation", model="microsoft/FrogMini-14B-2510")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("microsoft/FrogMini-14B-2510")
model = AutoModelForCausalLM.from_pretrained("microsoft/FrogMini-14B-2510", 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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use microsoft/FrogMini-14B-2510 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "microsoft/FrogMini-14B-2510"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "microsoft/FrogMini-14B-2510",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/microsoft/FrogMini-14B-2510

SGLang

How to use microsoft/FrogMini-14B-2510 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 "microsoft/FrogMini-14B-2510" \
    --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": "microsoft/FrogMini-14B-2510",
		"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 "microsoft/FrogMini-14B-2510" \
        --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": "microsoft/FrogMini-14B-2510",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use microsoft/FrogMini-14B-2510 with Docker Model Runner:
```
docker model run hf.co/microsoft/FrogMini-14B-2510
```

MarcCote

chsingh commited on Jan 9

Commit

f9fbac6

verified ·

1 Parent(s): a0a332f

Create NOTICE.md (#1)

Browse files

- Create NOTICE.md (759f0c03ef4fda29f042c8d89d52a3b83b9b7e44)

Co-authored-by: Chinmay Singh <chsingh@users.noreply.huggingface.co>

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+# NOTICE
+This model release includes components derived from the **Qwen** model family.
+## Attribution
+The Qwen model is developed and maintained by Alibaba Cloud.
+Original source and documentation: [https://github.com/QwenLM](https://github.com/QwenLM)
+## License
+The Qwen model is distributed under the **Apache License 2.0**.
+Full license text: [https://www.apache.org/licenses/LICENSE-2.0](https://www.apache.org/licenses/LICENSE-2.0)
+## Modifications
+This release may include fine-tuning, additional training, or configuration changes applied to the original Qwen model.
+Such modifications are documented in the accompanying README.
+## Disclaimer
+The original Qwen authors and Alibaba Cloud are not responsible for any changes or downstream usage in this release.