Instructions to use Azma-AI/bart-conversation-summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Azma-AI/bart-conversation-summarizer 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="Azma-AI/bart-conversation-summarizer")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Azma-AI/bart-conversation-summarizer") model = AutoModelForSeq2SeqLM.from_pretrained("Azma-AI/bart-conversation-summarizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 390 Bytes
453692c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"add_prefix_space": false,
"bos_token": "<s>",
"cls_token": "<s>",
"eos_token": "</s>",
"errors": "replace",
"mask_token": "<mask>",
"model_max_length": 1024,
"name_or_path": "facebook/bart-large-xsum",
"pad_token": "<pad>",
"sep_token": "</s>",
"special_tokens_map_file": null,
"tokenizer_class": "BartTokenizer",
"trim_offsets": true,
"unk_token": "<unk>"
}
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