Does this project only work on linux?

[xhz2003]

How to run this biomedgpt big model locally? Any recommended links to related tutorials?

[taokz]

Currently, the Fairseq version is complete but works only on Linux due to limitations with Fairseq itself. However, for inference, you can refer to the Colab example in the README, which uses the transformers library and can be executed on other operating systems.

In addition, could you clarify which tutorials you’re looking for? Are you asking for a tutorial on Fairseq?

[xhz2003]

Currently, the Fairseq version is complete but works only on Linux due to limitations with Fairseq itself. However, for inference, you can refer to the Colab example in the README, which uses the transformers library and can be executed on other operating systems.

In addition, could you clarify which tutorials you’re looking for? Are you asking for a tutorial on Fairseq?

Thank you.
1, why after opening the train.py file inside pycharm:
from fairseq import (
# checkpoint_utils,
options, quantization_utils,
quantization_utils,
tasks,
utils.
)
Is the fairseq you mentioned a file directory? Why are all the references in parentheses missing? (That is, I looked at all the files you gave me and found that there are no files (options, quantization_utils,tasks,utils,) under the fairseq file.
2、What file is the main network structure of the BiomedGPT model you gave me?
3、Can I modify the network structure of BiomedGPT? And then fine-tune it so that it handles other related subtasks. Do you have any better suggestions?

[xhz2003]

Currently, the Fairseq version is complete but works only on Linux due to limitations with Fairseq itself. However, for inference, you can refer to the Colab example in the README, which uses the transformers library and can be executed on other operating systems.

In addition, could you clarify which tutorials you’re looking for? Are you asking for a tutorial on Fairseq?

May I ask, in which file path are your trained models saved? I want to fine tune him.

[taokz]

1. There are separate files for tasks, utils, models, etc. I’m not sure why PyCharm is reporting errors—it could be due to an incorrectly configured environment.

2. The model definition can be found in models/ofa/ofa.py.

3. Yes, feel free to modify the structure. If you’d like to add new tasks, you can create a new dataset and task by adding Python files to the data and tasks directories.

4. The checkpoints are stored on both HuggingFace and Dropbox. Please refer to the README file and follow the steps outlined there.

[xhz2003]

In the path of models/ofa you mentioned, the directories at the same level as it include clip, taming, as well as init.py, search.py, sequence_gemerator.py, what is the connection and difference between them? Can you briefly describe the relationship between the various files throughout the project? Which ones need core attention?

[taokz]

The sequence_generator.py script is used to decode or generate outputs based on specified hyperparameters, such as model selection and search strategies (e.g., beam search defined in search.py). The taming module, inherited from VQGAN (https://github.com/CompVis/taming-transformers), is used to encode image patches for preprocessing tasks (refer to masked image modeling in the paper) or to generate image patches. The clip module defines image encoders, such as ResNet and ViT, for training.