- Libraries
- Transformers
How to use zelalt/Chatbot_T5-Prmtrs with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="zelalt/Chatbot_T5-Prmtrs") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("zelalt/Chatbot_T5-Prmtrs")
model = AutoModelForSeq2SeqLM.from_pretrained("zelalt/Chatbot_T5-Prmtrs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use zelalt/Chatbot_T5-Prmtrs with vLLM:
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zelalt/Chatbot_T5-Prmtrs"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "zelalt/Chatbot_T5-Prmtrs",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'Use Docker
docker model run hf.co/zelalt/Chatbot_T5-Prmtrs
- SGLang
How to use zelalt/Chatbot_T5-Prmtrs 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 "zelalt/Chatbot_T5-Prmtrs" \
--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": "zelalt/Chatbot_T5-Prmtrs",
"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 "zelalt/Chatbot_T5-Prmtrs" \
--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": "zelalt/Chatbot_T5-Prmtrs",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}' - Docker Model Runner
How to use zelalt/Chatbot_T5-Prmtrs with Docker Model Runner:
docker model run hf.co/zelalt/Chatbot_T5-Prmtrs
