Add pipeline tag, library name and license

This PR adds the pipeline tag, the library name and the license to the model card metadata.

README.md

@@ -1,3 +1,9 @@
+---
+library_name: transformers
+pipeline_tag: feature-extraction
+license: apache-2.0
+---
+
 # DPLM
 DPLM (diffusion protein language model) is a versatile protein language model that demonstrates strong generative and predictive capabilities for protein sequences. Specifically, DPLM exhibits impressive performance in protein sequence generation, motif scaffolding, inverse folding, and representation learning.
 For more detailed information about DPLM, please refer to our paper [Diffusion Language Models Are Versatile Protein Learners](https://arxiv.org/abs/2402.18567).
@@ -12,7 +18,6 @@ model_name = "airkingbd/dplm_650m"
 dplm = DiffusionProteinLanguageModel.from_pretrained(model_name)
 ```
 
-
 All DPLM checkpoints are available in the table below:
 | Model size | Num layers | Num parameters |
 |------------------------------|----|----------|
@@ -20,5 +25,4 @@ All DPLM checkpoints are available in the table below:
 | [dplm_650m](https://huggingface.co/airkingbd/dplm_650m) | 33 | 650M    | 
 | [dplm_150m](https://huggingface.co/airkingbd/dplm_150m) | 30 | 150M    | 
 
-
 **News**: welcome to check our new work [DPLM-2: A Multimodal Diffusion Protein Language Model](https://huggingface.co/papers/2410.13782), a multimodal protein foundation model that extends DPLM to simultaneously model, understand, and generate both sequences and structures!