Instructions to use zhihan1996/DNA_bert_6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zhihan1996/DNA_bert_6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="zhihan1996/DNA_bert_6", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("zhihan1996/DNA_bert_6", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("zhihan1996/DNA_bert_6", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Fix AutoModel not loading model correctly due to config_class inconsistency
#11
by liamclarkza - opened
This fixes an issue when using AutoModel to instantiate the model where the config class instantiated with the model is from the transformers library instead of the model's module. This causes the instantiation to fail with the error below. See this Github issue for more details.
Traceback (most recent call last):
model = AutoModel.from_pretrained("zhihan1996/DNA_bert_6", trust_remote_code=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".../lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 560, in from_pretrained
cls.register(config.__class__, model_class, exist_ok=True)
File ".../lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 586, in register
raise ValueError(
ValueError: The model class you are passing has a `config_class` attribute that is not consistent with the config class you passed (model has <class 'transformers.models.bert.configuration_bert.BertConfig'> and you passed <class 'transformers_modules.zhihan1996.DNA_bert_6.55e0c0eb7b734c8b9b77bc083bf89eb6fbda1341.configuration_bert.BertConfig'>. Fix one of those so they match!