README.md

metadata

license: other
license_name: helpingai
license_link: LICENSE.md
pipeline_tag: text-generation
tags:
  - HelpingAI
  - Emotionally Intelligent
  - EQ
datasets:
  - OEvortex/SentimentSynth
  - JeanKaddour/minipile
  - OEvortex/vortex-mini
  - OEvortex/EmotionalIntelligence-75K
  - Abhaykoul/EMOTIONS
  - Abhaykoul/human-emotion
language:
  - en

HelpingAI2-4x6B : Emotionally Intelligent Conversational AI

Usage Code

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load the HelpingAI2-4x6B  model
model = AutoModelForCausalLM.from_pretrained("Abhaykoul/HelpingAI2-4x6B ", trust_remote_code=True)
# Load the tokenizer
tokenizer = AutoTokenizer.from_pretrained("Abhaykoul/HelpingAI2-4x6B ", trust_remote_code=True)


# Define the chat input
chat = [
    { "role": "system", "content": "You are HelpingAI, an emotional AI. Always answer my questions in the HelpingAI style." },
    { "role": "user", "content": "I'm excited because I just got accepted into my dream school! I wanted to share the good news with someone." }
]

inputs = tokenizer.apply_chat_template(
    chat,
    add_generation_prompt=True,
    return_tensors="pt"
).to(model.device)


# Generate text
outputs = model.generate(
    inputs,
    max_new_tokens=256,
    do_sample=True,
    temperature=0.6,
    top_p=0.9,
    eos_token_id=tokenizer.eos_token_id, 
)


response = outputs[0][inputs.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True))