Comments (2)
voidful
commented on September 1, 2024
Hi
You can check flan-t5 in README, it is Seq2SeqLM model.
https://github.com/voidful/TextRL#example---flan-t5
colab example:
https://colab.research.google.com/drive/1DYHt0mi6cyl8ZTMJEkMNpsSZCCvR4jM1?usp=sharing
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janpf
commented on September 1, 2024
Oh sorry, I missed that. I only scanned the imports and it looked like the FlanT5 is used as a decoder-only architecture 👀
from transformers import AutoModelForCausalLM, AutoTokenizer
[...]
model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base")Thanks for your quick reply, looks promising :)
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Related Issues (20)
- Backward compatibility HOT 2
- About the compare_sample HOT 1
- i get error when i use elon example HOT 6
- Text generation models generating repeated/duplicate text/sentences. HOT 3
- Are there any examples for T5 or Bart? Why T5 and bart give the same output before/after training? HOT 2
- Update interval HOT 3
- Documentation on Methodology HOT 1
- Support for other PFRL Algorithms HOT 2
- Text generation after period/full-stop (".")
- ValueError: Expected parameter logits HOT 5
- Reward policy agent environment is not training with Finetuned model HOT 1
- Does the package support automatic multi-gpu? HOT 2
- unfreeze_layer_from_past parameter HOT 4
- Problems in the inference process
- Fix Reward Calculation in `example/2022-12-10-textrl-elon-musk.ipynb` HOT 1
- AttributeError: 'MyRLEnv' object has no attribute 'num_envs' HOT 2
- AttributeError: module 'numpy' has no attribute '_no_nep50_warning' HOT 1
- It needs a license HOT 1
- AssertionError HOT 3
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