model could not load after finetuning
#2
by
zguo0525
- opened
Hey I wonder if anyone has experienced this issue before when loading a fine-tuned llama 2 model
Some weights of the model checkpoint at ../../vicuna4tools/output/llama-2-7b-hf/total_IC_train_clean were not used when initializing LlamaForCausalLM: ['_flat_param']
- This IS expected if you are initializing LlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing LlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Some weights of LlamaForCausalLM were not initialized from the model checkpoint at ../../vicuna4tools/output/llama-2-7b-hf/total_IC_train_clean and are newly initialized: ['layers.15.self_attn.rotary_emb.inv_freq', 'layers.2.self_attn.k_proj.weight',
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
Hey I wonder if anyone has experienced this issue before when loading a fine-tuned llama 2 model
Some weights of the model checkpoint at ../../vicuna4tools/output/llama-2-7b-hf/total_IC_train_clean were not used when initializing LlamaForCausalLM: ['_flat_param']
- This IS expected if you are initializing LlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing LlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Some weights of LlamaForCausalLM were not initialized from the model checkpoint at ../../vicuna4tools/output/llama-2-7b-hf/total_IC_train_clean and are newly initialized: ['layers.15.self_attn.rotary_emb.inv_freq', 'layers.2.self_attn.k_proj.weight',
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
I have no idea