Summarization
Transformers
PyTorch
TensorFlow
JAX
Rust
Safetensors
English
bart
text2text-generation
Eval Results (legacy)
Instructions to use facebook/bart-large-cnn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/bart-large-cnn with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="facebook/bart-large-cnn")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("facebook/bart-large-cnn") model = AutoModelForSeq2SeqLM.from_pretrained("facebook/bart-large-cnn") - Inference
- Notebooks
- Google Colab
- Kaggle
vocab size wrong in facebook/bart-large-cnn
#101
by silverbeats - opened
I met the following error.
/pytorch/aten/src/ATen/native/cuda/IndexKernelUtils.cu:16: vectorized_gather_kernel: block: [726,0,0], thread: [223,0,0] Assertion `ind >=0 && ind < ind_dim_size && "vectorized gather kernel index out of bounds"`failed.`
During debug, something goes wrong at change input_ids to embedding. Finally, I found that the vocab.json has 50265 tokens, but the vocab_size in config.json is 50264.