Comments (4)
Hi, thanks for reporting this.
Size mismatch would definitely be one big issue. Since you're trying to run the recovery script, which is essentially running weights addition under the hood, we expect the base checkpoint to be exactly the original 7b checkpoint in hugging face format.
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OK, then I need to find a way to obtain Llama-1 rather than Llama-2. Any hints are welcome.
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I think there are third-party weights on spaces if you search for llama there. Let me know how it goes!
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I tried the llama-7b-hf from https://huggingface.co/decapoda-research/llama-7b-hf which looks like it is a copy of the original. Still, I get the exact same error as in my first comment above.
Can you point me to any version of llama that should work, so that I can rule out that it is a problem with the model?
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Related Issues (20)
- [Bug] Error importing is_deepspeed_zero3_enabled HOT 1
- Question about KL term HOT 1
- Reproducibility of pretuned reward model
- KeyError: 'llama' in /recover_model_weights.py HOT 2
- Confusing detail preference mapping HOT 1
- recover_model_weights.py gives WARNING:root:Your base LLaMA checkpoint is converted with transformers==4.27.0.dev0
- Huge memory demand of recover_model_weights.py?
- RewardModel.from_pretrained() loads redundant weights (incurs extra ~30GB of RAM)
- Why use FSDP instead of Deepspeed? HOT 2
- lower cuda version? HOT 1
- integrity_check error with sft10k
- score with reward model HOT 2
- RecursionError: maximum recursion depth exceeded
- BaseAnnotator.__init__() got an unexpected keyword argument 'other_keys_to_keep' HOT 4
- PairwiseAutoAnnotator always "Annotating 0 examples with gpt4_3" HOT 1
- Repeated Deprecation Error HOT 3
- Error downloading pre-trained weights
- Using pretrained models HOT 3
- Inquiry Regarding Supervised Fine-Tuning with AlpacaFarm Framework for Pythia Models HOT 1
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