error when loading the model
#2
by
PerRing
- opened
WARNING:accelerate.utils.modeling:The model weights are not tied. Please use the `tie_weights` method before using the `infer_auto_device` function.
Loading checkpoint shards: 0%
0/6 [00:00<?, ?it/s]
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-5-c1b45b9f685e> in <cell line: 3>()
1 from transformers import AutoProcessor,AutoTokenizer, AutoModelForCausalLM, AutoConfig,CLIPImageProcessor, LlamaForCausalLM, LlamaModel, LlavaForConditionalGeneration, LlavaConfig, CLIPVisionConfig, LlamaConfig, CLIPVisionModel, LlavaProcessor
2 import torch
----> 3 LlavaModel = LlavaForConditionalGeneration.from_pretrained("llava-hf/llava-1.5-13b-hf", torch_dtype=torch.float16, device_map='auto')
3 frames
/usr/local/lib/python3.10/dist-packages/accelerate/utils/modeling.py in set_module_tensor_to_device(module, tensor_name, device, value, dtype, fp16_statistics)
283 if value is not None:
284 if old_value.shape != value.shape:
--> 285 raise ValueError(
286 f'Trying to set a tensor of shape {value.shape} in "{tensor_name}" (which has shape {old_value.shape}), this look incorrect.'
287 )
ValueError: Trying to set a tensor of shape torch.Size([32064, 5120]) in "weight" (which has shape torch.Size([32128, 5120])), this look incorrect.
'llava-hf/llava-1.5-7b-hf' is loaded without any error, but when load 'llava-hf/llava-1.5-13b-hf', this error happen
cc
@ybelkada
quick fix is to use set the vocab_size to 32064
in the call to from_pretrained
ybelkada
changed discussion status to
closed