yhavinga/mc4_nl_cleaned
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How to use Alqayed2024/gpt2-cpt-dutch with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="Alqayed2024/gpt2-cpt-dutch") # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Alqayed2024/gpt2-cpt-dutch")
model = AutoModelForCausalLM.from_pretrained("Alqayed2024/gpt2-cpt-dutch")How to use Alqayed2024/gpt2-cpt-dutch with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Alqayed2024/gpt2-cpt-dutch"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "Alqayed2024/gpt2-cpt-dutch",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/Alqayed2024/gpt2-cpt-dutch
How to use Alqayed2024/gpt2-cpt-dutch with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "Alqayed2024/gpt2-cpt-dutch" \
--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": "Alqayed2024/gpt2-cpt-dutch",
"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 "Alqayed2024/gpt2-cpt-dutch" \
--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": "Alqayed2024/gpt2-cpt-dutch",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'How to use Alqayed2024/gpt2-cpt-dutch with Docker Model Runner:
docker model run hf.co/Alqayed2024/gpt2-cpt-dutch
This model is a fine-tuned version of gpt2 on the ['yhavinga/mc4_nl_cleaned'] dataset. It has been trained using TRL.
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="Alqayed2024/gpt2-cpt-dutch", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
This model was trained with SFT.
Cite TRL as:
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
Base model
openai-community/gpt2