abertsch72 / abertsch72/unlimiformer
Error Encountered While Running 'run_generation.py' Script
- Linguagem predominante
- Python
- Estrelas
- 1.1k
- Forks
- 78
- Métricas de merge de PRs
- Nenhum PR com merge em 30d
Descrição
I am facing an issue when attempting to run the 'run_generation.py' script from the 'unlimiformer/src' directory. This script is crucial for my work with **Unlimiformer on Google Colab**, and I need assistance in resolving the problem.
When executing the following command:
```
python src/run_generation.py --model_type llama --model_name_or_path meta-llama/Llama-2-13b-chat-hf \
--prefix "[INST] <>\n You are a helpful assistant. Answer with detailed responses according to the entire instruction or question. \n<>\n\n Summarize the following book: " \
--prompt example_inputs/harry_potter_full.txt \
--suffix " [/INST]" --test_unlimiformer --fp16 --length 200 --layer_begin 16 \
--index_devices 1 --datastore_device 1
```
the script runs on Google Colab, but it abruptly terminates with the following error message:
```
10/05/2023 11:16:12 - WARNING - __main__ - device: cuda, n_gpu: 1, 16-bits training: True
Using pad_token, but it is not set yet.
^C
```
The script utilizes the 'cuda' device, and I have one GPU ('n_gpu: 1') available for the process.
I am enabling 16-bits training with the '--fp16' flag.
The script also specifies various parameters, including 'length,' 'layer_begin,' 'index_devices,' and 'datastore_device.'
The issue arises when running the script but does not provide a clear indication of the problem's root cause.
Guia de contribuição
Nenhum guia de contribuição indexado para este repositório
Direção de pesquisa
The error occurs in run_generation.py when using the Llama model. Start by examining the script in src/run_generation.py, focusing on the tokenizer setup and pad_token configuration. Check the model loading and initialization steps, and run a minimal test to see if the pad_token warning is the cause of termination. Look for any existing tests or similar issues in the repository.
Escrita pelo modelo de indexação a partir do texto da issue.
Avaliação
- Domínio
- ai, machine-learning
- Tipo de issue
- Bug
- Dificuldade
- 3/5
- Tempo estimado
- 1-2 dias
- Status de atividade
- Estagnada
- Clareza
- Razoavelmente clara
- Facilidade para iniciantes
- 45/100