Transformers
PyTorch
Safetensors
English
t5
text2text-generation
qa
askscience
lfqa
information retrieval
text-generation-inference
Instructions to use pszemraj/t5-base-askscience with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pszemraj/t5-base-askscience with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("pszemraj/t5-base-askscience") model = AutoModelForSeq2SeqLM.from_pretrained("pszemraj/t5-base-askscience", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -33,7 +33,7 @@ inference:
|
|
| 33 |
|
| 34 |
# t5 - base- askscience
|
| 35 |
|
| 36 |
-
- [t5-v1_1](google/t5-v1_1-base) trained on the entirety of the _askscience_ sub-section of the eli5 dataset for one epoch.
|
| 37 |
- compare to bart on eli5 [here](https://huggingface.co/yjernite/bart_eli5)
|
| 38 |
- note that for the inference API, the model is restricted to outputting 64 tokens - by using the model in python with the transformers library, you can get longer outputs.
|
| 39 |
|
|
|
|
| 33 |
|
| 34 |
# t5 - base- askscience
|
| 35 |
|
| 36 |
+
- [t5-v1_1](https://huggingface.co/google/t5-v1_1-base) trained on the entirety of the _askscience_ sub-section of the eli5 dataset for one epoch.
|
| 37 |
- compare to bart on eli5 [here](https://huggingface.co/yjernite/bart_eli5)
|
| 38 |
- note that for the inference API, the model is restricted to outputting 64 tokens - by using the model in python with the transformers library, you can get longer outputs.
|
| 39 |
|