Instructions to use kmfoda/long-t5-tglobal-xxl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kmfoda/long-t5-tglobal-xxl with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kmfoda/long-t5-tglobal-xxl") model = AutoModelForSeq2SeqLM.from_pretrained("kmfoda/long-t5-tglobal-xxl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Fix code example
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README.md
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@@ -39,8 +39,8 @@ The model is mostly meant to be fine-tuned on a supervised dataset. See the [mod
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```python
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from transformers import AutoTokenizer, LongT5Model
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tokenizer = AutoTokenizer.from_pretrained("google/
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model = LongT5Model.from_pretrained("google/
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inputs = tokenizer("Hello, my dog is cute", return_tensors="pt")
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outputs = model(**inputs)
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```python
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from transformers import AutoTokenizer, LongT5Model
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tokenizer = AutoTokenizer.from_pretrained("google/long-t5-tglobal-large")
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model = LongT5Model.from_pretrained("google/long-t5-tglobal-large")
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inputs = tokenizer("Hello, my dog is cute", return_tensors="pt")
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outputs = model(**inputs)
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