Update README.md

README.md

@@ -8,31 +8,41 @@ pipeline_tag: text-generation
 widget:
 - text: Introduction to Vertex AI Feature Store
   example_title: Example 1
-- text: Introduction to JAX
+- text: What are Kubeflow Components?
   exmaple_title: Example 2
 tags:
 - Text-Generation
-- Scripts
 ---
-# Script_GPT
-## Model Details
-The Script_GPT is a language model developed using the Hugging Face Transformers library. It is trained on a custom dataset of YouTube scripts and can be used to generate new scripts for YouTube videos.
-The model is based on the GPT architecture and has a total of 117M parameters. 
 
-## Intended Use
-The Script_GPT model is intended to be used for generating scripts for YouTube videos. It can be used by content creators, marketers, and other individuals who want to produce high-quality scripts for their YouTube channels.
+# SCRIPTGPT
 
-## Limitations and Bias
-The Script_GPT model is trained on a custom dataset of YouTube scripts, which may not represent all possible types of videos on the platform. As a result, the model may have limitations when generating scripts for certain types of videos.
-Additionally, like all language models, the Script_GPT model may exhibit bias in its outputs based on the biases present in the training data. It is important to review and evaluate the model's outputs to ensure that they are free from bias and harmful content.
+Pretrained model on the English language using a causal language modeling (CLM) objective. It was introduced in
+[this paper](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf)
+and first released at [this page](https://openai.com/blog/better-language-models/).
 
-## Training Data
-The Script_GPT model was trained on a custom dataset of YouTube scripts, which was collected from a variety of sources, including popular YouTube channels and public scripts available online.
-The dataset consists of only 6 scripts. The scripts are biased towards the Youtuber Ali Abdala.
+## Model description
+ScriptGPT is a language model trained on a dataset of 5,000 YouTube videos that explain artificial intelligence (AI) concepts.
+ScriptGPT is a Causal language transformer. The model resembles the GPT2 architecture, 
+the model is a Causal Language model meaning it predicts the probability of a sequence of words based on the preceding words in the sequence. 
+It generates a probability distribution over the next word given the previous words, without incorporating future words.
 
-## How to Use
-_Installation_
-To use the Script_GPT model, you first need to install the Hugging Face Transformers library:
+The goal of ScriptGPT is to generate scripts for AI videos that are coherent, informative, and engaging. 
+This can be useful for content creators who are looking for inspiration or who want to automate the process of generating video scripts. 
+To use ScriptGPT, users can provide a prompt or a starting sentence, and the model will generate a sequence of words that follow the context and style of the training data.
+
+The current model is the smallest one with 124 million parameters (ScriptGPT)
+
+More models are coming soon...
+
+## Intended uses
+The intended uses of ScriptGPT include generating scripts for videos that explain artificial intelligence concepts, providing inspiration for content creators, and 
+automating the process of generating video scripts. 
+
+
+## How to use
+You can use this model directly with a pipeline for text generation.
+
+1. __Load Model__
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
@@ -40,11 +50,31 @@ tokenizer = AutoTokenizer.from_pretrained("SRDdev/Script_GPT")
 model = AutoModelForCausalLM.from_pretrained("SRDdev/Script_GPT")
 ```
 
-_Generating Scripts_
-To generate scripts using the Script_GPT model, you can use the following code:
+2. __Pipeline__
 ```python
 from transformers import pipeline
-generator = pipeline('text-generation', model="SRDdev/Script_GPT",tokenizer="SRDdev/Script_GPT")
-text = generator("Write a Script on Deep Learning ", max_length=1000, do_sample=True)[0]['generated_text']
-print(text)
+generator = pipeline('text-generation', model= model , tokenizer=tokenizer)
+
+context = "Introduction to Vertex AI Feature Store"
+length_to_generate = 200 
+
+script = generator(context, max_length=length_to_generate, do_sample=True)[0]['generated_text']
+```
+<p style="opacity: 0.8">Keeping the context more technical and related to AI will generate better outputs</p>
+
+## Limitations and bias
+> The model is trained on Youtube Scripts and will work better for that. It may also generate random information and users should be aware of that and cross-validate the results.
+
+The used is linked [here](https://www.kaggle.com/datasets/jfcaro/5000-transcripts-of-youtube-ai-related-videos)
+
+## Citations
+```
+@model{
+        Name=Shreyas Dixit
+        framework=Pytorch
+        Year=Jan 2023
+        Pipeline=text-generation
+        Github=https://github.com/SRDdev
+        LinkedIn=https://www.linkedin.com/in/srddev
+      }
 ```