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
| <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> |