Abirate/english_quotes
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How to use sr5434/gptQuotes with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="sr5434/gptQuotes") # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("sr5434/gptQuotes")
model = AutoModelForCausalLM.from_pretrained("sr5434/gptQuotes")How to use sr5434/gptQuotes with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "sr5434/gptQuotes"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "sr5434/gptQuotes",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/sr5434/gptQuotes
How to use sr5434/gptQuotes with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "sr5434/gptQuotes" \
--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": "sr5434/gptQuotes",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'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 "sr5434/gptQuotes" \
--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": "sr5434/gptQuotes",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'How to use sr5434/gptQuotes with Docker Model Runner:
docker model run hf.co/sr5434/gptQuotes
This model is a fine-tuned version of facebook/opt-350m on an Abirate's English Quotes dataset.
Generating quotes with AI
A demo of this AI is availible in a Huggingface Space. Do not use the version attached to this model, as it doesn't work.
from transformers import pipeline
ai = pipeline('text-generation',model='sr5434/gptQuotes', tokenizer='facebook/opt-350m', device=-1)#,config={'max_length':45})
while True:
result = ai(input("Prompt>>>"))[0]['generated_text']
print(result)
The following hyperparameters were used during training: