Instructions to use SkillForge45/CyberFuture-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SkillForge45/CyberFuture-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SkillForge45/CyberFuture-3")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SkillForge45/CyberFuture-3", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use SkillForge45/CyberFuture-3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SkillForge45/CyberFuture-3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SkillForge45/CyberFuture-3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SkillForge45/CyberFuture-3
- SGLang
How to use SkillForge45/CyberFuture-3 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 "SkillForge45/CyberFuture-3" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SkillForge45/CyberFuture-3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "SkillForge45/CyberFuture-3" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SkillForge45/CyberFuture-3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SkillForge45/CyberFuture-3 with Docker Model Runner:
docker model run hf.co/SkillForge45/CyberFuture-3
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4bc48f4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | <!DOCTYPE html>
<html>
<head>
<title>CyberFuture-3</title>
</head>
<body>
<div id="chat"></div>
<input type="text" id="input" placeholder="Type your question...">
<button onclick="sendMessage()">Send</button>
<button onclick="startVoice()">Voice</button>
<script>
async function sendMessage() {
const input = document.getElementById('input').value;
const response = await fetch('http://localhost:8000/chat/', {
method: 'POST',
headers: {
'Content-Type': 'application/x-www-form-urlencoded',
},
body: `prompt=${encodeURIComponent(input)}&use_web=true`
});
const data = await response.json();
document.getElementById('chat').innerHTML += `<p>You: ${input}</p>`;
document.getElementById('chat').innerHTML += `<p>Bot: ${data.response}</p>`;
}
async function startVoice() {
// You would need to add proper voice recording implementation
alert("Voice recording would be implemented here");
}
</script>
</body>
</html> |