Instructions to use nferruz/ProtGPT2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nferruz/ProtGPT2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nferruz/ProtGPT2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("nferruz/ProtGPT2") model = AutoModelForCausalLM.from_pretrained("nferruz/ProtGPT2") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use nferruz/ProtGPT2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nferruz/ProtGPT2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nferruz/ProtGPT2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/nferruz/ProtGPT2
- SGLang
How to use nferruz/ProtGPT2 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 "nferruz/ProtGPT2" \ --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": "nferruz/ProtGPT2", "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 "nferruz/ProtGPT2" \ --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": "nferruz/ProtGPT2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use nferruz/ProtGPT2 with Docker Model Runner:
docker model run hf.co/nferruz/ProtGPT2
Problems encountered when fine-tuning model validation
01/31/2024 22:44:19 - INFO - main - *** Evaluate ***
[INFO|trainer.py:3283] 2024-01-31 22:44:19,667 >> ***** Running Evaluation *****
[INFO|trainer.py:3285] 2024-01-31 22:44:19,667 >> Num examples = 0
[INFO|trainer.py:3288] 2024-01-31 22:44:19,667 >> Batch size = 1
Traceback (most recent call last):
File "run_clm.py", line 670, in
main()
File "run_clm.py", line 636, in main
metrics = trainer.evaluate()
File "/root/autodl-tmp/shiyang/software/protgpt2/lib/python3.8/site-packages/transformers/trainer.py", line 3136, in evaluate
output = eval_loop(
File "/root/autodl-tmp/shiyang/software/protgpt2/lib/python3.8/site-packages/transformers/trainer.py", line 3325, in evaluation_loop
loss, logits, labels = self.prediction_step(model, inputs, prediction_loss_only, ignore_keys=ignore_keys)
File "/root/autodl-tmp/shiyang/software/protgpt2/lib/python3.8/site-packages/transformers/trainer.py", line 3495, in prediction_step
has_labels = False if len(self.label_names) == 0 else all(inputs.get(k) is not None for k in self.label_names)
File "/root/autodl-tmp/shiyang/software/protgpt2/lib/python3.8/site-packages/transformers/trainer.py", line 3495, in
has_labels = False if len(self.label_names) == 0 else all(inputs.get(k) is not None for k in self.label_names)
AttributeError: 'NoneType' object has no attribute 'get'
Dear author, I encountered such an error when fine-tuning the model, and I have been unable to solve it effectively. Sincerely wanting to ask for your help
It seems you don’t have any sequences in your validation dataset.