Liang Zhang

thats the reason why i failed, thanks very much.

i have a similar issue too ``` │ 153 │ def optimizer_step(self, optimizer: optim.Optimizer, **kwargs) -> None: │ │ ❱ 154 │ │ optimizer.step() │ │ 155 │ │ │...

Hi @ViCtOr-dev13 , You are right. The chart-to-table task requires the model to extract all the data presented in the chart, but the summarization task doesn't. This is related to...

Hi @ViCtOr-dev13, We just released the training code in this repo. Please try to pull the latest code. Have fun!

Hi @MonolithFoundation, We plan to release the training data and code in early June. Stay tuned!

Hi @MonolithFoundation , We have just released the data at [mPLUG/TinyChartData](https://huggingface.co/datasets/mPLUG/TinyChartData). Have fun!

Hi @matsuobasho, TinyChart can be able to run on the CPU theoretically, but it may not yet supported by this code. I am going to check it and update the...

> I'm running the inference notebook and just changed device to 'cpu': > > ```python > import torch > from PIL import Image > from tinychart.model.builder import load_pretrained_model > from...

你好， tinychart采用插值的方式对tinyllava的position embedding进行扩展。你可以试试以下代码： ``` import math import torch import torch.nn.functional as F def get_abs_pos(abs_pos, tgt_size): # abs_pos: L, C # tgt_size: M # return: M, C src_size = int(math.sqrt(abs_pos.size(0))) tgt_size...

Hi @LilDevsy0117, Our model is based on TinyLlava, which uses Phi-2 as the LLM. It uses Byte-level BPE and can be naturally applied to other languages including Korean after fine-tuning...