---
license: apache-2.0
language:
  - en
library_name: transformers
tags:
  - mistral
  - fine-tuned
  - chatbot
  - AI tools
  - instruction-tuned
  - gguf
pipeline_tag: text-generation
model-index:
  - name: Mistral Fine-Tuned Chatbot
    results: []
---

# 🔧 Mistral Fine-Tuned Chatbot for AI Tool Queries

This model is a fine-tuned version of [`TheBloke/OpenHermes-2.5-Mistral-7B-GGUF`](https://huggingface.co/TheBloke/OpenHermes-2.5-Mistral-7B-GGUF) on a custom dataset of AI tool instructions. It's designed to behave as a conversational assistant that can answer technical queries related to popular AI tools.

## 🧠 Model Details

- **Base model**: `OpenHermes-2.5-Mistral-7B-GGUF`
- **Fine-tuned on**: Custom dataset of structured JSONL instructions
- **Training platform**: Google Colab Pro (A100 GPU)
- **Fine-tuning method**: Supervised fine-tuning using 🤗 Transformers + Datasets

## 📂 Example Use Cases

- 🛠️ Recommend and explain AI tools for different tasks
- 💬 Simulate chatbot responses about ML libraries, APIs, and platforms
- 🧪 Useful for education, technical support, and integration with AI assistants

## 💻 Usage

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained("amalsp/mistral-finetuned-chatbot")
tokenizer = AutoTokenizer.from_pretrained("amalsp/mistral-finetuned-chatbot")

prompt = "What AI tool can I use for image generation?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=150)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))