Comments (1)
You should be using the same class to load the model e.g. GPT2HeadWithValueModel
or AutoModelForCausalLM
(although I haven't tested the latter). AutoModel
will load the model without LM head.
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Related Issues (20)
- AttributeError: 'PPOv2Trainer' object has no attribute 'deepspeed' HOT 3
- Incorrect Doc String for `SFTConfig` HOT 2
- plz make GPOTrainer! (Generalized Preference Optimization)
- AttributeError: 'PPOv2Trainer' object has no attribute 'deepspeed' HOT 3
- ConstantLengthDataset should shuffle the order of samples before packing HOT 2
- The ppo_trainer.generate() call results in an error. HOT 2
- DPOTrainer failed on training Custom Mixture of Experts model with config output_router_logits=True
- Disable the dropout by default in Online DPO HOT 1
- RLOOTrainer & PPOv2Trainer - Modify Name for W&B Logged Table HOT 3
- PPOv2Trainer & RLOOTrainer - Add Safety Check that `policy` object != `ref_policy` object HOT 2
- Always allow `ref_model=None` HOT 5
- Reward model HOT 4
- [DPOTrainer] Tokenizer calculation fail during Q+A concat HOT 3
- Model does not generate eos when SFTTrainer with setup_chat_format is used HOT 1
- Deepspeed Zero2 not working when using DPOTrainer HOT 3
- Discrepancy in LLaMA 3.1 performance when using custom trainer and SFTTrainer HOT 7
- why does the ppo calculate advantage reversed the index?
- [Tracking issue] General dataset support
- `GKDTrainer`
- Uneven model loading HOT 12
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