Text Generation
Transformers
Safetensors
English
DexV1
fill-mask
DexAI
Dexai
dexai
DEX-Modle
IND-Dec
AI-Dexhat
CSAI
CybersecurityDex
Dexhat
text-generation-inference
Ghosthets
ghosthets-dex
Dex-ghosthets
ghosthets-ai
ghosthets-dex-ai
Dex-community
Dextron
Instructions to use ghosthets/Dex with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghosthets/Dex with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ghosthets/Dex")# Load model directly from transformers import AutoModelWithLMHead model = AutoModelWithLMHead.from_pretrained("ghosthets/Dex", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use ghosthets/Dex with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ghosthets/Dex" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ghosthets/Dex", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ghosthets/Dex
- SGLang
How to use ghosthets/Dex 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 "ghosthets/Dex" \ --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": "ghosthets/Dex", "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 "ghosthets/Dex" \ --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": "ghosthets/Dex", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ghosthets/Dex with Docker Model Runner:
docker model run hf.co/ghosthets/Dex
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Curious Minds
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#🧠 Creator
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Gaurav Chouhan
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aka ghosthets
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Curious Minds
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⚡ Optimized for edge devices — This model is fine-tuned to run efficiently even on low-power systems like Raspberry Pi Zero W, 2W, and similar micro boards. While it's currently trained on limited data, we plan to expand its training set soon, making it even more accurate, interactive, and capable of deeper conversations and secure communications.
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#🧠 Creator
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Gaurav Chouhan
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aka ghosthets
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