Transformers
PyTorch
t5
text2text-generation
biology
protein
protein language model
protein embedding
text-generation-inference
Instructions to use ElnaggarLab/ankh2-ext1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ElnaggarLab/ankh2-ext1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ElnaggarLab/ankh2-ext1") model = AutoModelForSeq2SeqLM.from_pretrained("ElnaggarLab/ankh2-ext1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -9,11 +9,7 @@ datasets:
|
|
| 9 |
- agemagician/uniref50
|
| 10 |
---
|
| 11 |
|
| 12 |
-
#
|
| 13 |
-
|
| 14 |
-
The model will be uploaded soon, please stay tuned.
|
| 15 |
-
|
| 16 |
-
# ANKH2-Large model
|
| 17 |
|
| 18 |
Pretrained model on protein sequences using a masked language modeling (MLM) objective. It was introduced in
|
| 19 |
[this paper](https://arxiv.org/abs/2301.06568) and first released in
|
|
|
|
| 9 |
- agemagician/uniref50
|
| 10 |
---
|
| 11 |
|
| 12 |
+
# ANKH2-extended1 model
|
|
|
|
|
|
|
|
|
|
|
|
|
| 13 |
|
| 14 |
Pretrained model on protein sequences using a masked language modeling (MLM) objective. It was introduced in
|
| 15 |
[this paper](https://arxiv.org/abs/2301.06568) and first released in
|