Instructions to use Ayansk11/FinSenti-MobileLLM-R1-950M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Ayansk11/FinSenti-MobileLLM-R1-950M with Transformers:

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

pipe = pipeline("text-generation", model="Ayansk11/FinSenti-MobileLLM-R1-950M")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Ayansk11/FinSenti-MobileLLM-R1-950M")
model = AutoModelForCausalLM.from_pretrained("Ayansk11/FinSenti-MobileLLM-R1-950M")
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 Ayansk11/FinSenti-MobileLLM-R1-950M with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Ayansk11/FinSenti-MobileLLM-R1-950M"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Ayansk11/FinSenti-MobileLLM-R1-950M",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Ayansk11/FinSenti-MobileLLM-R1-950M

SGLang

How to use Ayansk11/FinSenti-MobileLLM-R1-950M 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 "Ayansk11/FinSenti-MobileLLM-R1-950M" \
    --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": "Ayansk11/FinSenti-MobileLLM-R1-950M",
		"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 "Ayansk11/FinSenti-MobileLLM-R1-950M" \
        --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": "Ayansk11/FinSenti-MobileLLM-R1-950M",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Ayansk11/FinSenti-MobileLLM-R1-950M with Docker Model Runner:
```
docker model run hf.co/Ayansk11/FinSenti-MobileLLM-R1-950M
```

Ayansk11 commited on 23 days ago

Commit

0e5d6ed

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1 Parent(s): f49e498

Update model card

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README.md CHANGED Viewed

@@ -221,6 +221,6 @@ Apache 2.0, same as the base model.
 ## Acknowledgements
-Trained on the Indiana University BigRed200 cluster (account `r01510`).
 Thanks to the Unsloth and TRL teams for the trainer stack, and to the
 Qwen / DeepSeek teams for the base models.

 ## Acknowledgements
+Trained on the Indiana University BigRed200 cluster.
 Thanks to the Unsloth and TRL teams for the trainer stack, and to the
 Qwen / DeepSeek teams for the base models.