Create README.md

README.md

@@ -0,0 +1,23 @@
+---
+- Text Generation
+- PyTorch
+- Transformers
+- gpt_neo
+- text generation
+---
+
+## Petrained Model Description: GPT-Neo (Open Source Version of GPT-3)
+Generative Pre-trained Transformer 3 (GPT-3) is an autoregressive language model that uses deep learning to produce human-like text.
+It is the third-generation language prediction model in the GPT-n series (and the successor to GPT-2) created by OpenAI
+
+GPT-Neo (125M) is a transformer model designed using EleutherAI's replication of the GPT-3 architecture. GPT-Neo refers to the class of models, while 125M represents the number of parameters of this particular pre-trained model.
+and first released in this [repository](https://github.com/EleutherAI/gpt-neo). 
+
+
+## Fine-tuned Model Description: GPT-3 fine-tuned Multi-XScience
+The Open Source version of GPT-3: GPT-Neo(125M) has been fine-tuned on dataset called "Multi-XScience": [Multi-XScience_Repository](https://github.com/yaolu/Multi-XScience)  
+
+I deployed it using Google "Material Design" (on Anvil): [Abir Scientific text Generator](https://abir-scientific-text-generator.anvil.app/)  
+
+By fine-tuning GPT-Neo on Multi-XScience dataset, the model is now able to generate scientific texts(even better than GPT-J(6B)
+Here's a demonstration video for this. [Video real-time Demontration](https://www.youtube.com/watch?v=XP8uZfnCYQI)