Transformers
JAX
Safetensors
English
t5
text2text-generation
biomedical
clinical
ul2
encoder-decoder
pretraining
medical
text-generation-inference
Instructions to use Siddharth63/medul2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Siddharth63/medul2-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Siddharth63/medul2-base") model = AutoModelForSeq2SeqLM.from_pretrained("Siddharth63/medul2-base") - Notebooks
- Google Colab
- Kaggle
Commit ·
7568e8c
1
Parent(s): 3114e37
Update ul2_tasks2.py
Browse files- ul2_tasks2.py +1 -1
ul2_tasks2.py
CHANGED
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@@ -61,7 +61,7 @@ def target_to_key(x, key_map, target_key):
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return {**key_map, target_key: x}
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dataset_name = "
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dataset_params = {"from_disk_path": dataset_name}
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if "from_disk_path" in dataset_params:
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return {**key_map, target_key: x}
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+
dataset_name = "/home/sdeshpande/data/medical_dataset"
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dataset_params = {"from_disk_path": dataset_name}
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if "from_disk_path" in dataset_params:
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