Instructions to use trl-internal-testing/dummy-GPT2-correct-vocab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trl-internal-testing/dummy-GPT2-correct-vocab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="trl-internal-testing/dummy-GPT2-correct-vocab") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("trl-internal-testing/dummy-GPT2-correct-vocab") model = AutoModelForCausalLM.from_pretrained("trl-internal-testing/dummy-GPT2-correct-vocab") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use trl-internal-testing/dummy-GPT2-correct-vocab with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "trl-internal-testing/dummy-GPT2-correct-vocab" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "trl-internal-testing/dummy-GPT2-correct-vocab", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/trl-internal-testing/dummy-GPT2-correct-vocab
- SGLang
How to use trl-internal-testing/dummy-GPT2-correct-vocab 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 "trl-internal-testing/dummy-GPT2-correct-vocab" \ --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": "trl-internal-testing/dummy-GPT2-correct-vocab", "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 "trl-internal-testing/dummy-GPT2-correct-vocab" \ --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": "trl-internal-testing/dummy-GPT2-correct-vocab", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use trl-internal-testing/dummy-GPT2-correct-vocab with Docker Model Runner:
docker model run hf.co/trl-internal-testing/dummy-GPT2-correct-vocab
Dummy GPT2 for TRL testing
from transformers import AutoTokenizer, GPT2Config, GPT2LMHeadModel
config = GPT2Config(n_positions=512, n_embd=32, n_layer=5, n_head=4, n_inner=37, pad_token_id=1023, is_decoder=True)
model = GPT2LMHeadModel(config)
tokenizer = AutoTokenizer.from_pretrained("openai-community/gpt2")
model_id = "trl-internal-testing/dummy-GPT2-correct-vocab"
model.push_to_hub(model_id)
tokenizer.chat_template = "{% for message in messages %}{% if message['role'] == 'user' %}{{ ' ' }}{% endif %}{{ message['content'] }}{% if not loop.last %}{{ ' ' }}{% endif %}{% endfor %}{{ eos_token }}"
tokenizer.push_to_hub(model_id)
config.push_to_hub(model_id)
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