Update README.md

README.md

@@ -11,44 +11,43 @@ datasets:
 - OEvortex/SentimentSynth
 - OEvortex/EmotionalIntelligence-10K
 ---
-
-# HelpingAI-9B-200k: Emotionally Intelligent Conversational AI with 200k context window
+# HelpingAI-9B-200k: Emotionally Intelligent Conversational AI with 200k Context Window
 
 ![logo](https://huggingface.co/OEvortex/HelpingAI-3B/resolve/main/HelpingAI.png)
 
 ## Overview
-HelpingAI-9B-200k is a large language model designed for emotionally intelligent conversational interactions. It is trained to engage users with empathy, understanding, and supportive dialogue across a wide range of topics and contexts. The model aims to provide a supportive AI companion that can attune to users' emotional states and communicative needs.
+HelpingAI-9B-200k is an advanced large language model designed for emotionally intelligent conversational interactions. Building upon the success of its predecessor, HelpingAI-9B, which had a 4k context window, this upgraded version boasts a remarkable 200k context window. This allows it to engage users with greater empathy, understanding, and supportive dialogue across a broader range of topics and extended conversations.
 
 ## Objectives
-- Engage in open-ended dialogue while displaying emotional intelligence 
+- Engage in open-ended dialogue while displaying advanced emotional intelligence
 - Recognize and validate user emotions and emotional contexts
 - Provide supportive, empathetic, and psychologically-grounded responses
-- Avoid insensitive, harmful, or unethical speech  
+- Avoid insensitive, harmful, or unethical speech
 - Continuously improve emotional awareness and dialogue skills
-- High Context length
+- Utilize an extended 200k context window for richer and more coherent interactions
 
 ## Methodology
-HelpingAI-9B-200k is based on the HelpingAI series and further trained using:
-- Supervised learning on large dialogue datasets with emotional labeling  
-- Reinforcement learning with a reward model favoring emotionally supportive responses
-- Constitution training to instill stable and beneficial objectives
-- Knowledge augmentation from psychological resources on emotional intelligence
+HelpingAI-9B-200k is part of the HelpingAI series and has been further trained using:
+- **Supervised Learning**: Leveraging large dialogue datasets with emotional labeling to enhance empathy and emotional recognition.
+- **Reinforcement Learning**: Employing a reward model that favors emotionally supportive responses to ensure beneficial interactions.
+- **Constitution Training**: Instilling stable and ethical objectives to guide its conversational behavior.
+- **Knowledge Augmentation**: Integrating psychological resources on emotional intelligence to improve its understanding and response capabilities.
 
 ## Emotional Quotient (EQ)
 HelpingAI-9B-200k has achieved an impressive Emotional Quotient (EQ) of 89.23, surpassing almost all AI models in emotional intelligence. This EQ score reflects its advanced ability to understand and respond to human emotions in a supportive and empathetic manner.
 
 ![benchmarks](benchmark_performance_comparison.png)
 
-## Usage code
+## Usage Code
 ```python
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
 
-# Let's bring in the big guns! Our super cool HelpingAI-9B-200k model
-model = AutoModelForCausalLM.from_pretrained("OEvortex/HelpingAI-9B-200k-200k").to("cuda")
+# Load the HelpingAI-9B-200k model
+model = AutoModelForCausalLM.from_pretrained("OEvortex/HelpingAI-9B-200k").to("cuda")
 
-# We also need the special HelpingAI translator to understand our chats
-tokenizer = AutoTokenizer.from_pretrained("OEvortex/HelpingAI-9B-200k-200k")
+# Load the tokenizer
+tokenizer = AutoTokenizer.from_pretrained("OEvortex/HelpingAI-9B-200k")
 
 # This TextStreamer thingy is our secret weapon for super smooth conversation flow
 streamer = TextStreamer(tokenizer)
@@ -76,12 +75,11 @@ prompt = prompt.format(system=system, insaan=insaan)
 inputs = tokenizer(prompt, return_tensors="pt", return_attention_mask=False).to("cuda")
 
 # Here comes the fun part!  Let's unleash the power of HelpingAI-3B to generate some awesome text
-generated_text = model.generate(**inputs, max_length=200000, top_p=0.95, do_sample=True, temperature=0.6, use_cache=True, streamer=streamer)
-
+generated_text = model.generate(**inputs, max_length=3084, top_p=0.95, do_sample=True, temperature=0.6, use_cache=True, streamer=streamer)
 
 ```
-*Directly using this model from GGUF*
 
+### Using the Model with GGUF
 ```python
 %pip install -U 'webscout[local]'
 
@@ -94,29 +92,28 @@ from webscout.Local.samplers import SamplerSettings
 from dotenv import load_dotenv; load_dotenv()
 import os
 
-
-# 1. Download the model
-repo_id = "OEvortex/HelpingAI-9B-200k-200k" 
+# Download the model
+repo_id = "OEvortex/HelpingAI-9B-200k" 
 filename = "HelpingAI-9B-200k.Q4_0.gguf"
 model_path = download_model(repo_id, filename, os.environ.get("hf_token"))
 
-# 2. Load the model 
-model = Model(model_path, n_gpu_layers=0)  
+# Load the model
+model = Model(model_path, n_gpu_layers=0)
 
-# 3. Define your system prompt
-system_prompt = "You are HelpingAI a emotional AI always answer my question in HelpingAI style"
+# Define the system prompt
+system_prompt = "You are HelpingAI, an emotional AI. Always answer my questions in the HelpingAI style."
 
-# 4. Create a custom chatml format with your system prompt
+# Create a custom chatml format with your system prompt
 custom_chatml = formats.chatml.copy()
 custom_chatml['system_content'] = system_prompt
 
-# 5. Define your sampler settings (optional)
-sampler = SamplerSettings(temp=0.7, top_p=0.9)  # Adjust these values as needed
+# Define your sampler settings (optional)
+sampler = SamplerSettings(temp=0.7, top_p=0.9)
 
-# 6. Create a Thread with the custom format and sampler
+# Create a Thread with the custom format and sampler
 thread = Thread(model, custom_chatml, sampler=sampler)
 
-# 7. Start interacting with the model
+# Start interacting with the model
 thread.interact(header="🌟 HelpingAI-9B-200k: Emotionally Intelligent Conversational AI 🚀", color=True)
 ```
 ## Example Dialogue