README.md

---
tags:
- customer-support
- LLaMA
- fine-tuned
- AI
- chatbot
- ai-agent
license: apache-2.0
library_name: transformers
model_creator: Ansah AI
model_type: causal-lm
finetuned_from: meta-llama/Llama-1-1B
datasets:
- custom-dataset
language:
- en
base_model:
- meta-llama/Llama-3.2-1B-Instruct
---

```markdown
 Ansah E1: Fine-Tuned Customer Support Model

 Model Overview
Ansah E1 is a fine-tuned version of Meta’s LLaMA 1B-intruct,
 built for automating customer support across industries.
It provides fast, accurate, and context-aware responses, 
making it ideal for businesses seeking AI-driven support solutions.  

While it is highly optimized for e-commerce,
 it can also be used for SaaS, IT support, and enterprise service automation.
Unlike traditional cloud-based models, Ansah E1 runs locally, 
ensuring data privacy, lower operational costs, and reduced latency.  



 Key Features
- Accurate and context-aware responses  
  - Understands structured and unstructured customer queries  
  - Maintains conversation memory for multi-turn interactions  

- Automated ticket escalation when used with langchain  or other frameworks
  - Detects critical cases and escalates them intelligently  
  - Reduces workload by handling repetitive issues autonomously  

- Local deployment and data privacy  
  - Runs entirely on-premises for full data control  
  - Eliminates external cloud dependencies, ensuring security  

- Optimized for efficient performance  
  - Works smoothly on consumer-grade GPUs and high-performance CPUs  
  - Available in 4-bit GGUF format for lightweight, optimized deployment  

- Seamless API and tool integration  
  - Can integrate with e-commerce platforms, SaaS tools, and IT support systems  
  - Supports tool-calling functions to automate business workflows  



 Model Details
- Base Model: Meta LLaMA 1B  
- Fine-Tuned Data: Customer support logs, e-commerce transactions, and business service inquiries  
- Primary Use Cases:  
  - E-Commerce: Order tracking, refunds, cancellations, and payment assistance  
  - IT and SaaS Support: AI-powered help desks and troubleshooting  
  - Enterprise Automation: On-prem AI assistants for business operations  
- Hardware Compatibility:  
  - Optimized for local GPU and CPU deployment  
  - Available in GGUF format for lightweight, high-speed inference  



 Available Model Formats  
 Full Precision Model (Hugging Face Transformers)
Repository: [Ansah E1](https://huggingface.co/Ansah-AI/E1)  
- Best suited for high-accuracy, real-time inference  
- Runs efficiently with 4-bit or 8-bit quantization for optimal performance  

 4-Bit GGUF Model for Lightweight Deployment
Repository: [Ansah E1 - 4bit GGUF](https://huggingface.co/dheerajdasari/E1-Q4_K_M-GGUF)  
- Designed for low-resource environments  
- Ideal for Llama.cpp, KoboldAI, and local AI inference engines  



 How to Use  

 Using the Full Precision Model
python
from transformers import AutoTokenizer, AutoModelForCausalLM

 Load the fine-tuned model and tokenizer
tokenizer = AutoTokenizer.from_pretrained("Ansah-AI/E1")
model = AutoModelForCausalLM.from_pretrained("Ansah-AI/E1")

- For optimized inference, use 4-bit or 8-bit quantization via bitsandbytes  



 Using the GGUF 4-Bit Model (For Llama.cpp and Local Inference)
bash
 Download the GGUF model
wget https://huggingface.co/dheerajdasari/E1-Q4_K_M-GGUF/resolve/main/E1-Q4_K_M.gguf

 Run using Llama.cpp
./main -m E1-Q4_K_M.gguf -p "Hello, how can I assist you?"

- Works with Llama.cpp, KoboldAI, and other local inference frameworks  
- Perfect for low-power devices or edge deployment  



 Conclusion  
Ansah E1 is a scalable, private, and efficient AI model designed to automate customer support across multiple industries. It eliminates cloud dependencies, ensuring cost-effective and secure deployment while providing fast, intelligent, and reliable support automation.  

Try it now:  
[Ansah E1 (Full Model)](https://huggingface.co/Ansah-AI/E1)  
[Ansah E1 - 4bit GGUF](https://huggingface.co/dheerajdasari/E1-Q4_K_M-GGUF)