Comments (1)
Thanks for raising this, something to look into. Could you print out the data inputs that are fed to the LLM to better see the issue? On that note, also, I think not all of the entries have multi-turn answers
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Related Issues (20)
- Missing python dependencies for running pretrain tutorial HOT 1
- Finetune lora max_seq_length error HOT 4
- Continue finetuning HOT 2
- Support non-int batch_size argument "auto" with litgpt evaluate HOT 3
- Command -> litgpt download openlm-research/open_llama_13b gives error: Unrecognized arguments: openlm-research/open_llama_13b HOT 4
- Finetuning with multiple gpus extemely slow HOT 2
- Batched inference on a single node with multiple GPUs HOT 9
- Gradient Accumulation Step under Multi-node Pretaining HOT 5
- Support a new model HOT 7
- Compiled inference failed: "Global state changed while dynamo tracing" HOT 1
- serving with multi-GPU HOT 2
- Enable multi-turn prompts for supported LLMs HOT 1
- numpy 2.0.0 support HOT 4
- FileNotFoundError: [Errno 2] No such file or directory: 'microsoft/phi-2/lit_model.pth' HOT 3
- add support for Qwen 2 HOT 1
- Could we pass number of litdata workers in litgpt pretrain? HOT 5
- PermissionError: [Errno 13] Permission denied: 'nvidia-smi' HOT 10
- Logit .dtype is always float32 irregardless of model weight dtype HOT 3
- Catastrophic forgetting occur when I perform continued pre-training on Llama 3 HOT 11
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