BertLMHeadModel.from_pretrained("bert-base-uncased", config=encoder_config)
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 882
- Forks
- 76
- PR merge metrics
- No merged PRs in 30d
Description
https://github.com/OpenMOSS/AnyGPT/blob/main/seed2/seed_qformer/blip2.py中的
Qformer = BertLMHeadModel.from_pretrained("bert-base-uncased", config=encoder_config)
加载预训练的bert时，由于服务器不能访问hugging face，所以自己提前下载了
https://huggingface.co/google-bert/bert-base-uncased/tree/main，
然后报错
Some weights of BertLMHeadModel were not initialized from the model checkpoint at 本地地址 and are newly initialized: xx
请问是我下载的bert-base-uncased不对吗？
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start at seed2/seed_qformer/blip2.py and inspect the BertLMHeadModel.from_pretrained call using the local bert-base-uncased checkpoint. Reproduce the reported initialization warning and compare the locally downloaded files with what this loading entry point expects; done means determining whether the checkpoint is appropriate and documenting the cause.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100