MaartenGr / MaartenGr/BERTopic
RuntimeError: The size of tensor a (678) must match the size of tensor b (512) at non-singleton dimension 1
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 7.8k
- Forks
- 920
- Avg merge
- 22h 24m
- Merged PRs (30d)
- 5
Description
Hi!, I'm using the pipeline to load the model of BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext from huggingface, but it seems to have gone wrong. The following is my code and the bug. Please help me.
embedding_model = pipeline("feature-extraction", model=r"D:\A-编程\生物医药\BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext"）
topic_model = BERTopic(
language='english',
embedding_model=embedding_model,
#verbose=True
)
topics,probilities=topic_model.fit_transform(df_value['text'].tolist())
RuntimeError: The size of tensor a (678) must match the size of tensor b (512) at non-singleton dimension 1
Contributor guide
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 by reproducing the reported failure with the BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext pipeline and the BERTopic configuration shown in the issue. Trace the call from embedding_model through topic_model.fit_transform and inspect where tensor dimensions 678 and 512 are produced. Done means the documented setup runs without this size-mismatch RuntimeError.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- huggingface, python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100