I successfully finetuned the model using stated steps, then i reload the model and merge it with Lora weight top prepare for inferencing. The merge code as below :
However i received an error while inferencing :
The model 'LlamaForCausalLM' is not supported for token-classification. Supported models are ['AlbertForTokenClassification', 'BertForTokenClassification', 'BigBirdForTokenClassification', 'BioGptForTokenClassification', 'BloomForTokenClassification', 'BrosForTokenClassification', 'CamembertForTokenClassification', 'CanineForTokenClassification', 'ConvBertForTokenClassification', 'Data2VecTextForTokenClassification', 'DebertaForTokenClassification', 'DebertaV2ForTokenClassification', 'DistilBertForTokenClassification', 'ElectraForTokenClassification', 'ErnieForTokenClassification', 'ErnieMForTokenClassification', 'EsmForTokenClassification', 'FalconForTokenClassification', 'FlaubertForTokenClassification', 'FNetForTokenClassification', 'FunnelForTokenClassification', 'GPT2ForTokenClassification', 'GPT2ForTokenClassification', 'GPTBigCodeForTokenClassification', 'GPTNeoForTokenClassification', 'GPTNeoXForTokenClassification', 'IBertForTokenClassification', 'LayoutLMForTokenClassification', 'LayoutLMv2ForTokenClassification', 'LayoutLMv3ForTokenClassification', 'LiltForTokenClassification', 'LongformerForTokenClassification', 'LukeForTokenClassification', 'MarkupLMForTokenClassification', 'MegaForTokenClassification', 'MegatronBertForTokenClassification', 'MobileBertForTokenClassification', 'MPNetForTokenClassification', 'MptForTokenClassification', 'MraForTokenClassification', 'NezhaForTokenClassification', 'NystromformerForTokenClassification', 'QDQBertForTokenClassification', 'RemBertForTokenClassification', 'RobertaForTokenClassification', 'RobertaPreLayerNormForTokenClassification', 'RoCBertForTokenClassification', 'RoFormerForTokenClassification', 'SqueezeBertForTokenClassification', 'XLMForTokenClassification', 'XLMRobertaForTokenClassification', 'XLMRobertaXLForTokenClassification', 'XLNetForTokenClassification', 'XmodForTokenClassification', 'YosoForTokenClassification'].
Asking to truncate to max_length but no maximum length is provided and the model has no predefined maximum length. Default to no truncation.
Kindly guide me for better inferencing steps. Thank you
I successfully finetuned the model using stated steps, then i reload the model and merge it with Lora weight top prepare for inferencing. The merge code as below :
However i received an error while inferencing :
The model 'LlamaForCausalLM' is not supported for token-classification. Supported models are ['AlbertForTokenClassification', 'BertForTokenClassification', 'BigBirdForTokenClassification', 'BioGptForTokenClassification', 'BloomForTokenClassification', 'BrosForTokenClassification', 'CamembertForTokenClassification', 'CanineForTokenClassification', 'ConvBertForTokenClassification', 'Data2VecTextForTokenClassification', 'DebertaForTokenClassification', 'DebertaV2ForTokenClassification', 'DistilBertForTokenClassification', 'ElectraForTokenClassification', 'ErnieForTokenClassification', 'ErnieMForTokenClassification', 'EsmForTokenClassification', 'FalconForTokenClassification', 'FlaubertForTokenClassification', 'FNetForTokenClassification', 'FunnelForTokenClassification', 'GPT2ForTokenClassification', 'GPT2ForTokenClassification', 'GPTBigCodeForTokenClassification', 'GPTNeoForTokenClassification', 'GPTNeoXForTokenClassification', 'IBertForTokenClassification', 'LayoutLMForTokenClassification', 'LayoutLMv2ForTokenClassification', 'LayoutLMv3ForTokenClassification', 'LiltForTokenClassification', 'LongformerForTokenClassification', 'LukeForTokenClassification', 'MarkupLMForTokenClassification', 'MegaForTokenClassification', 'MegatronBertForTokenClassification', 'MobileBertForTokenClassification', 'MPNetForTokenClassification', 'MptForTokenClassification', 'MraForTokenClassification', 'NezhaForTokenClassification', 'NystromformerForTokenClassification', 'QDQBertForTokenClassification', 'RemBertForTokenClassification', 'RobertaForTokenClassification', 'RobertaPreLayerNormForTokenClassification', 'RoCBertForTokenClassification', 'RoFormerForTokenClassification', 'SqueezeBertForTokenClassification', 'XLMForTokenClassification', 'XLMRobertaForTokenClassification', 'XLMRobertaXLForTokenClassification', 'XLNetForTokenClassification', 'XmodForTokenClassification', 'YosoForTokenClassification'].
Asking to truncate to max_length but no maximum length is provided and the model has no predefined maximum length. Default to no truncation.
Kindly guide me for better inferencing steps. Thank you