Add nequip.

docs/notebooks.md

@@ -2,23 +2,61 @@
 
 Quick start using GoogleColab notebook examples
 
-1. [Analyzing_data_in_the_JARVIS_Leaderboard.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Analyzing_data_in_the_JARVIS_Leaderboard.ipynb)
-2. [Upload_benchmark_to_jarvis_leaderboard.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Upload_benchmark_to_jarvis_leaderboard.ipynb)
-3. [alignn_jarvis_leaderboard.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/alignn_jarvis_leaderboard.ipynb)
-4. [kgcnn_jarvis_leaderboard.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/kgcnn_jarvis_leaderboard.ipynb)
-5. [MatMiner_on_JARVIS_DFT.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/MatMiner_on_JARVIS_DFT.ipynb)
-6. [Train ALIGNN-FF](https://github.com/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Train_ALIGNNFF_Mlearn.ipynb)
-7. [Train ALLEGRO-FF](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Train_MLFF_ALLEGRO.ipynb)
-8. [AtomVision_Image_Classification.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/AtomVisionImageClassification.ipynb)
-9. [Text-generation ChemNLP/HuggingFace.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/ChemNLP_TitleToAbstract.ipynb)
-10. [Inverse design of superconductors](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/cdvae_example.ipynb)
-11. [QuantumComputation for FCC Aluminum.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Qiskit_based_electronic_bandstructure_latest_qiskit.ipynb)
-12. [Pretrained CHGNet Prediction.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/chgnet_prediction.ipynb)
-13. [Pretrained OpenCatalystProject Model.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/ocp_load_pretrained_models.ipynb)
-14. [GPAW colab.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/GPAW_Colab.ipynb)
-15. [Quantum Espresso colab.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/LK99_GoogleColab_QE.ipynb)
-16. [ocp20_load_pretrained_models.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/ocp_load_pretrained_models.ipynb)
-17. [MatGL-FF_Mlearn.ipynb](https://github.com/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Matgl_mlearn.ipynb)
-18. [SNAP-FF_Mlearn.ipynb](https://github.com/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/snap_mlearn.ipynb)
-
-For additional notebooks, visit [JARVIS-Tools-Notebooks](https://github.com/JARVIS-Materials-Design/jarvis-tools-notebooks) collections with more than 60 colab notebooks. 
+## General 
+
+[Analyzing_data_in_the_JARVIS_Leaderboard.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Analyzing_data_in_the_JARVIS_Leaderboard.ipynb)
+
+[Upload_benchmark_to_jarvis_leaderboard.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Upload_benchmark_to_jarvis_leaderboard.ipynb)
+
+## Elecronic structure
+
+[GPAW colab.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/GPAW_Colab.ipynb)
+
+[Quantum Espresso colab.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/LK99_GoogleColab_QE.ipynb)
+
+
+## Machine-learning regression model for atomistic properties
+
+[alignn_jarvis_leaderboard.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/alignn_jarvis_leaderboard.ipynb)
+
+[kgcnn_jarvis_leaderboard.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/kgcnn_jarvis_leaderboard.ipynb)
+
+[MatMiner_on_JARVIS_DFT.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/MatMiner_on_JARVIS_DFT.ipynb)
+
+## Machine learning force-field
+
+[Train ALIGNN-FF.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Train_ALIGNNFF_Mlearn.ipynb)
+
+[Train ALLEGRO-FF.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Train_MLFF_ALLEGRO.ipynb)
+
+[Train NEQUIP-FF.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Train_MLFF_NEQUIP.ipynb)
+
+[Train CHGNet-FF.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Train_CHGNet.ipynb)
+
+[MatGL-FF_Mlearn.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Matgl_mlearn.ipynb)
+
+[SNAP-FF_Mlearn.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/snap_mlearn.ipynb)
+
+[Pretrained CHGNet Prediction.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/chgnet_prediction.ipynb)
+
+[Pretrained OpenCatalystProject Model.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/ocp_load_pretrained_models.ipynb)
+
+[ocp20_load_pretrained_models.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/ocp_load_pretrained_models.ipynb)
+
+## Image analytics
+
+[AtomVision_Image_Classification.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/AtomVisionImageClassification.ipynb)
+
+## Text generation
+
+[Text-generation ChemNLP/HuggingFace.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/ChemNLP_TitleToAbstract.ipynb)
+
+## Inverse design of atomic structures
+
+[Inverse design of superconductors.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/cdvae_example.ipynb)
+
+## Quantu computation
+
+[QuantumComputation for FCC Aluminum.ipynb](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Qiskit_based_electronic_bandstructure_latest_qiskit.ipynb)
+
+For additional notebooks, visit [JARVIS-Tools-Notebooks](https://github.com/JARVIS-Materials-Design/jarvis-tools-notebooks) collections with more than 100 colab notebooks. 

jarvis_leaderboard/contributions/nequip_mlearn/metadata.json

@@ -0,0 +1,31 @@
+{
+    "model_name": "NEQUIP",
+    "project_url": "https://www.nature.com/articles/s41467-023-36329-y",
+    "date_submitted": "07-22-2023",
+    "author_email": "[email protected]",
+    "database_version": "12-12-2022",
+    "team_name": "MIR",
+    "time_taken_seconds": {
+        "AI-MLFF-energy-alignn_ff_db-test-mae.csv.zip": "",
+        "AI-MLFF-energy-mlearn_Cu-test-mae.csv.zip": "",
+        "AI-MLFF-energy-mlearn_Ge-test-mae.csv.zip": "",
+        "AI-MLFF-energy-mlearn_Li-test-mae.csv.zip": "",
+        "AI-MLFF-energy-mlearn_Mo-test-mae.csv.zip": "",
+        "AI-MLFF-energy-mlearn_Ni-test-mae.csv.zip": "",
+        "AI-MLFF-energy-mlearn_Si-test-mae.csv.zip": "",
+        "AI-MLFF-forces-alignn_ff_db-test-multimae.csv.zip": "",
+        "AI-MLFF-forces-mlearn_Cu-test-multimae.csv.zip": "",
+        "AI-MLFF-forces-mlearn_Ge-test-multimae.csv.zip": "",
+        "AI-MLFF-forces-mlearn_Li-test-multimae.csv.zip": "",
+        "AI-MLFF-forces-mlearn_Mo-test-multimae.csv.zip": "",
+        "AI-MLFF-forces-mlearn_Ni-test-multimae.csv.zip": "",
+        "AI-MLFF-forces-mlearn_Si-test-multimae.csv.zip": ""
+    },
+    "language": "python",
+    "os": "linux",
+    "software_used": "allegro,jarvis-tools,numpy,scipy,torch,alignn",
+    "hardware_used": "nisaba-cluster at NIST, V100 Tesla GPU",
+    "git_url": [
+        "https://github.com/mir-group/nequip"
+    ]
+}