How to use from
SGLangInstall from pip and serve model
# Install SGLang from pip:
pip install sglang# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "marswallet/supportAI" \
--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": "marswallet/supportAI",
"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 "marswallet/supportAI" \
--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": "marswallet/supportAI",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'Quick Links
pipeline_tag: text-generation library_name: transformers tags: - gpt2 - text-generation
SupportAI 🤖
SupportAI is a fine-tuned GPT-2 model built to assist users with support and intent understanding tasks.
It can handle short conversations, detect user intent, and provide friendly, helpful replies.
Example
Input:
Author: marswallet
License: MIT
Base Model: GPT-2
Framework: Hugging Face Transformers
- Downloads last month
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# Gated model: Login with a HF token with gated access permission hf auth login