Summarization
PEFT
Arabic
English
bloomz
bloom
meeting summarization
messages summarization
text2text-generation
text-generation
Instructions to use mohamedemam/Arabic-meeting-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mohamedemam/Arabic-meeting-summarization with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigscience/bloomz-3b") model = PeftModel.from_pretrained(base_model, "mohamedemam/Arabic-meeting-summarization") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from mohamedemam/Arabic-meeting-summarization: direct link, hf CLI and curl.
- Browser
- Download file 443 Bytes
-
https://huggingface.co/mohamedemam/Arabic-meeting-summarization/resolve/main/adapter_model.bin
- Command line
-
hf download hf://mohamedemam/Arabic-meeting-summarization/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/mohamedemam/Arabic-meeting-summarization/resolve/main/adapter_model.bin
443 Bytes
- Xet hash:
- c320938e3fc30b4618917983e921399eb7675418277eb404dabd305711d7ec07
- Size of remote file:
- 443 Bytes
- SHA256:
- e5e1621f48d9ad8feb1d6d31050275f0aafd080c5c07153301fe2f48411f4406
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