Whether upon trying the inference API or running the code in “use with transformers” I get the following long error:
“Can’t load tokenizer using from_pretrained, please update its configuration: Can’t load tokenizer for ‘remi/bertabs-finetuned-extractive-abstractive-summarization’. If you were trying to load it from ‘Models - Hugging Face’, make sure you don’t have a local directory with the same name. Otherwise, make sure ‘remi/bertabs-finetuned-extractive-abstractive-summarization’ is the correct path to a directory containing all relevant files for a BertTokenizerFast tokenizer.”
This doesn’t just apply to this specific model but for many models I have tried to run. Is there any solution for this?
I have this same error. replying to get feedback.
Hi, can you try:
from transformers import BertForMaskedLM
model = BertForMaskedLM.from_pretrained("remi/bertabs-finetuned-extractive-abstractive-summarization")
This worked for me
@EssamWisam How were you able to solve this problem. I am facing the same issue. The code is working in one of the GPUs but when i try to run it azure gpu i am getting this issue
Network issues can also cause this issue.
In my case I solved it by setting proxy, maybe you can try to check your network.
"I encountered a similar error but was able to resolve it by referring to the Hugging Face documentation.
- Initially, access the Hugging Face hub via the notebook by executing the following commands:
!pip install huggingface_hub
from huggingface_hub import notebook_login
Note: Two types of tokens, namely ‘read’ and ‘write’, are generated in your huggingface hub. The ‘write’ token should be utilized for authorization.
- Begin by pushing the files associated with the model to the hub:
- Similarly, push the tokenizer-related files to the hub:
And that’s it, your problem is solved