Instructions to use Samuael/amharic-t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Samuael/amharic-t5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Samuael/amharic-t5") model = AutoModelForSeq2SeqLM.from_pretrained("Samuael/amharic-t5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload T5ForConditionalGeneration
Browse files- config.json +1 -0
- generation_config.json +1 -0
config.json
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@@ -15,6 +15,7 @@
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"is_encoder_decoder": true,
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"is_gated_act": false,
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"layer_norm_epsilon": 1e-06,
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"model_type": "t5",
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"num_decoder_layers": 6,
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"num_heads": 8,
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"is_encoder_decoder": true,
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"is_gated_act": false,
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"layer_norm_epsilon": 1e-06,
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"max_length": 300,
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"model_type": "t5",
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"num_decoder_layers": 6,
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"num_heads": 8,
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generation_config.json
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@@ -2,6 +2,7 @@
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"_from_model_config": true,
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"decoder_start_token_id": 0,
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"eos_token_id": 3,
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"pad_token_id": 0,
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"transformers_version": "4.38.2"
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}
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"_from_model_config": true,
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"decoder_start_token_id": 0,
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"eos_token_id": 3,
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"max_length": 300,
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"pad_token_id": 0,
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"transformers_version": "4.38.2"
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}
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