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declare-lab / flacuna

Flacuna was developed by fine-tuning Vicuna on Flan-mini, a comprehensive instruction collection encompassing various tasks. Vicuna is already an excellent writing assistant, and the intention behind Flacuna was to enhance Vicuna's problem-solving capabilities. To achieve this, we curated a dedicated instruction dataset called Flan-mini.
https://huggingface.co/declare-lab/flacuna-13b-v1.0
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Some weights of the model checkpoint at declare-lab/flacuna-13b-v1.0 were not used when initializing LlamaForCausalLM: #2

Open ayseozgun opened 1 year ago

ayseozgun commented 1 year ago

Hi,

I am trying to run the model on Sagemaker, but I am getting the following warning:

"Some weights of the model checkpoint at declare-lab/flacuna-13b-v1.0 were not used when initializing LlamaForCausalLM"

I tried two ways, but both of them gave same issue.(hf and github source code) How can I solve this? Can you help me please? Thanks

import torch from transformers import LlamaForCausalLM, LlamaTokenizer base_model = "declare-lab/flacuna-13b-v1.0" tokenizer = LlamaTokenizer.from_pretrained(base_model) model = LlamaForCausalLM.from_pretrained(base_model,torch_dtype=torch.float16, device_map="auto")

from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("declare-lab/flacuna-13b-v1.0") model = AutoModelForCausalLM.from_pretrained("declare-lab/flacuna-13b-v1.0",torch_dtype=torch.float16, device_map="auto")

deepanwayx commented 1 year ago

Hi, Flacuna is a LoRA-based model. You can refer to the flacuna.py file to see how we load the weights in self.model.

ayseozgun commented 1 year ago

Thanks for your response. Yes, I tried this way also, but did not work.

deepanwayx commented 1 year ago

Can you add the warning message here? The warning you are encountering should also show the parameter names for which the pre-trained weights were not loaded.

Also, assuming you have the peft_flacuna from this repo in your directory?

ayseozgun commented 1 year ago

I am working on Sagemaker Studio. I am trying to run the model directly there. The warning message is below(refer to flacuna.py). Thanks.

`Some weights of the model checkpoint at declare-lab/flacuna-13b-v1.0 were not used when initializing LlamaForCausalLM: ['base_model.model.model.layers.31.self_attn.k_proj.SCB', 'base_model.model.model.layers.36.self_attn.rotary_emb.inv_freq', 'base_model.model.model.layers.29.self_attn.v_proj.weight', 'base_model.model.model.layers.20.mlp.down_proj.SCB', 'base_model.model.model.layers.17.self_attn.o_proj.weight', 'base_model.model.model.layers.19.mlp.down_proj.weight', 'base_model.model.model.layers.39.self_attn.v_proj.weight', 'base_model.model.model.layers.39.self_attn.v_proj.SCB', 'base_model.model.model.layers.36.self_attn.v_proj.SCB', 'base_model.model.model.layers.22.self_attn.q_proj.lora_A.default.weight', 'base_model.model.model.layers.6.self_attn.v_proj.lora_A.default.weight', 'base_model.model.model.layers.22.mlp.up_proj.SCB', 'base_model.model.model.layers.5.self_attn.q_proj.weight', 'base_model.model.model.layers.8.mlp.down_proj.SCB', 'base_model.model.model.layers.39.mlp.down_proj.weight', 'base_model.model.model.layers.1.self_attn.v_proj.SCB', 'base_model.model.model.layers.11.mlp.down_proj.SCB', 'base_model.model.model.layers.3.self_attn.q_proj.lora_B.default.weight', 'base_model.model.model.layers.5.self_attn.o_proj.SCB', 'base_model.model.model.layers.35.input_layernorm.weight', 'base_model.model.model.layers.17.self_attn.v_proj.weight', 'base_model.model.model.layers.9.self_attn.q_proj.SCB', 'base_model.model.model.layers.16.mlp.down_proj.SCB', 'base_model.model.model.layers.36.self_attn.v_proj.weight', 'base_model.model.model.layers.9.self_attn.k_proj.weight', 'base_model.model.model.layers.31.post_attention_layernorm.weight', 'base_model.model.model.layers.28.mlp.down_proj.SCB', 'base_model.model.model.layers.37.self_attn.rotary_emb.inv_freq', 'base_model.model.model.layers.12.self_attn.q_proj.lora_B.default.weight', 'base_model.model.model.layers.23.mlp.gate_proj.SCB', 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deepanwayx commented 1 year ago

This warning should come when you try to initialize LlamaForCausalLMdirectly from "declare-lab/flacuna-13b-v1.0". In flacuna.py, we first initialize Llama from "TheBloke/vicuna-13B-1.1-HF" and then load the LoRA weights from our checkpoint. Otherwise, the state dict keys are not going to match.

Can you also post the full code snippet?

ayseozgun commented 1 year ago

import torch from transformers import LlamaForCausalLM, LlamaTokenizer base_model = "TheBloke/vicuna-13B-1.1-HF" tokenizer = LlamaTokenizer.from_pretrained(base_model) model = LlamaForCausalLM.from_pretrained(base_model,torch_dtype=torch.float16, device_map="auto")

it worked after closing instance and opening again. I did not understand what was wrong, but now it is all okay. Thank you so much