How to modify the weights of the LLM section
I have a fine-tuned version of Mistral-7B-Instruct who has an expanded word list. I would like to be able to use this fine-tuned version of Mistral-7B-Instruct instead of the original Mistral-7B-Instruct .
I tried loading it like this：
model = AutoModelForVision2Seq.from_pretrained("HuggingFaceM4/idefics2-8b",torch_dtype=torch.float16,device_map="auto",text_config = config)
but
it seems like you changed the vocab size (and thus the embedding matrix size). did you reflect that change in the config? in particular the vocab_size attribute
it seems like you changed the vocab size (and thus the embedding matrix size). did you reflect that change in the config? in particular the
vocab_sizeattribute
Thanks for the reply, this is my config for text_mode:
"architectures": [
"MistralForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": 1,
"eos_token_id": 2,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 32768,
"model_type": "mistral",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 8,
"rms_norm_eps": 1e-05,
"rope_theta": 10000.0,
"sliding_window": 4096,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.36.2",
"use_cache": true,
"vocab_size": 63872
Based on the error message, it seems that although I changed vocab_size=63872, transformers still loaded the model's original mistral model (vocab_size=32003)