Summarization
Transformers
PyTorch
TensorBoard
mt5
text2text-generation
fa
Abstractive Summarization
Generated from Trainer
Instructions to use ahmeddbahaa/mt5-base-finetuned-fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmeddbahaa/mt5-base-finetuned-fa 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="ahmeddbahaa/mt5-base-finetuned-fa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ahmeddbahaa/mt5-base-finetuned-fa") model = AutoModelForSeq2SeqLM.from_pretrained("ahmeddbahaa/mt5-base-finetuned-fa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ahmeddbahaa/mt5-base-finetuned-fa: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/ahmeddbahaa/mt5-base-finetuned-fa/resolve/main/training_args.bin
- Command line
-
hf download hf://ahmeddbahaa/mt5-base-finetuned-fa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ahmeddbahaa/mt5-base-finetuned-fa/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- 545dad4cd71943d53f6f71cf933a5252c42f97e32182bb9c3fbb49a37fdfd88a
- Size of remote file:
- 3.31 kB
- SHA256:
- 3e8827e7ecbe3851fa88b14a273b0f34fd6797cd25f60d595c1f5c28c837a264
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