Create README.md

README.md

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+---
+license: bsd
+tags:
+- chemistry
+- biology
+- protein
+- antibodies
+- antibody
+- light chain
+- AbLang
+- CDR
+- OAS
+---
+
+# AbLang model for light chains
+
+This is a huggingface version of AbLang: A language model for antibodies. It was introduced in
+[this paper](https://doi.org/10.1101/2022.01.20.477061) and first released in
+[this repository](https://github.com/oxpig/AbLang). This model is trained on uppercase amino acids: it only works with capital letter amino acids.
+
+
+# Intended uses & limitations
+
+The model could be used for protein feature extraction or to be fine-tuned on downstream tasks (TBA).
+
+### How to use
+
+Here is how to use this model to get the features of a given antibody sequence in PyTorch:
+
+```python
+from transformers import AutoModel, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained('qilowoq/AbLang_light')
+model = AutoModel.from_pretrained('qilowoq/AbLang_light', trust_remote_code=True)
+
+sequence_Example = ' '.join("DIQMTQSPSTLSASIGDTVRISCRASQSITGNWVAWYQQRPGKAPRLLIYRGAALLGGVPSRFSGSAAGTDFTLTIGNLQAEDFGTFYCQQYDTYPGTFGQGTKVEVKRTVAAPSVFIFPPSDEQLKSGTASVVCLLNNFYPREAKVQWKVDNALQSGNSQESVTEQDSKDSTYSLSSTLTLSKADYEKHKVYACEVTHQGLSSPVTKSFNR")
+encoded_input = tokenizer(sequence_Example, return_tensors='pt')
+model_output = model(encoded_input)
+```
+
+Sentence embeddings can be produced as follows:
+
+```python
+seq_embs = model_output.last_hidden_state[:, 0, :]
+```
+
+### Citation
+```
+@article{Olsen2022,
+  title={AbLang: An antibody language model for completing antibody sequences},
+  author={Tobias H. Olsen, Iain H. Moal and Charlotte M. Deane},
+  journal={bioRxiv},
+  doi={https://doi.org/10.1101/2022.01.20.477061},
+  year={2022}
+}
+```