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 (HF中国镜像站 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)
- Downloads last month
- 88
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.