Instructions to use radheneev/socpilot-0.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use radheneev/socpilot-0.5b with Transformers:

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

pipe = pipeline("text-generation", model="radheneev/socpilot-0.5b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("radheneev/socpilot-0.5b")
model = AutoModelForCausalLM.from_pretrained("radheneev/socpilot-0.5b", 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 radheneev/socpilot-0.5b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "radheneev/socpilot-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": "radheneev/socpilot-0.5b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/radheneev/socpilot-0.5b

SGLang

How to use radheneev/socpilot-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 "radheneev/socpilot-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": "radheneev/socpilot-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 "radheneev/socpilot-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": "radheneev/socpilot-0.5b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use radheneev/socpilot-0.5b with Docker Model Runner:
```
docker model run hf.co/radheneev/socpilot-0.5b
```

Radhe commited on Feb 9

Commit

8649409

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1 Parent(s): 2bd0133

Update README.md

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@@ -24,7 +24,7 @@ model-index:
       name: Security Alert Triage
     metrics:
     - type: accuracy
-      value: 99
       name: Priority Classification
 base_model:
 - Qwen/Qwen2.5-0.5B-Instruct
@@ -35,7 +35,7 @@ base_model:
 [![Model](https://img.shields.io/badge/🤗-Model-yellow)](https://huggingface.co/radherackbank/socpilot-0.5b)
 [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](LICENSE)
-[![Accuracy](https://img.shields.io/badge/accuracy-100%25-green)]()
 ## Overview

       name: Security Alert Triage
     metrics:
     - type: accuracy
+      value: 99.99
       name: Priority Classification
 base_model:
 - Qwen/Qwen2.5-0.5B-Instruct
 [![Model](https://img.shields.io/badge/🤗-Model-yellow)](https://huggingface.co/radherackbank/socpilot-0.5b)
 [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](LICENSE)
+[![Accuracy](https://img.shields.io/badge/accuracy-99.99%25-green)]()
 ## Overview