xtuner

/

llava-llama-3-8b-v1_1

like 120

Follow

xtuner 64

Could you add support for this?

Right now the config.json file in these repos is just the Llama 3 config.

When trying to load with LlavaForConditionalGeneraton.from_pretrained(), I get:

Some weights of LlavaForConditionalGeneration were not initialized from the model checkpoint at xtuner/llava-llama-3-8b-v1_1 and are newly initialized: ['model.language_model.lm_head.weight', 'model.language_model.model.embed_tokens.weight', 'model.language_model.model.layers.0.input_layernor

When trying to run evaluation, even just running the processor with:

inputs = processor(prompt, raw_image, return_tensors='pt').to(DEVICE, DTYPE)

I get:

ValueError                                Traceback (most recent call last)
Cell In[64], line 15
     13 raw_image = sample['image']
---> 15 inputs = processor(prompt, raw_image, return_tensors='pt').to(DEVICE, DTYPE)
     16 output = model.generate(**inputs, max_new_tokens=200, do_sample=False)
     17 print('model: ', processor.decode(output[0][2:], skip_special_tokens=True))

File /usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:2858, in PreTrainedTokenizerBase.__call__(self, text, text_pair, text_target, text_pair_target, add_special_tokens, padding, truncation, max_length, stride, is_split_into_words, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, **kwargs)
   2856     if not self._in_target_context_manager:
   2857         self._switch_to_input_mode()
-> 2858     encodings = self._call_one(text=text, text_pair=text_pair, **all_kwargs)
   2859 if text_target is not None:
   2860     self._switch_to_target_mode()

File /usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:2922, in PreTrainedTokenizerBase._call_one(self, text, text_pair, add_special_tokens, padding, truncation, max_length, stride, is_split_into_words, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, **kwargs)
   2916     raise ValueError(
   2917         "text input must be of type `str` (single example), `List[str]` (batch or single pretokenized example) "
   2918         "or `List[List[str]]` (batch of pretokenized examples)."
   2919     )
   2921 if text_pair is not None and not _is_valid_text_input(text_pair):
-> 2922     raise ValueError(
   2923         "text input must be of type `str` (single example), `List[str]` (batch or single pretokenized example) "
   2924         "or `List[List[str]]` (batch of pretokenized examples)."
   2925     )
   2927 if is_split_into_words:
   2928     is_batched = isinstance(text, (list, tuple)) and text and isinstance(text[0], (list, tuple))

ValueError: text input must be of type `str` (single example), `List[str]` (batch or single pretokenized example) or `List[List[str]]` (batch of pretokenized examples).