alpha-ai
/

AlphaAI-Chatty-INT2

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 ---
-library_name: transformers
 tags:
 - unsloth
-- trl
-- sft
 ---
-# Model Card for Model ID
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 ---
+base_model: meta-llama/Llama-3.2-3B-Instruct
 tags:
+- text-generation-inference
+- transformers
 - unsloth
+- llama
+- gguf
+license: apache-2.0
+language:
+- en
 ---
+<div align="center">
+<img src="https://cdn-uploads.huggingface.co/production/uploads/669777597cb32718c20d97e9/4emWK_PB-RrifIbrCUjE8.png"
+     alt="Title card"
+     style="width: 500px;
+            height: auto;
+            object-position: center top;">
+</div>
+# Uploaded Model
+- **Developed by:** Alpha AI
+- **License:** apache-2.0
+- **Finetuned from model:** meta-llama/Llama-3.2-3B-Instruct
+This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Hugging Face's TRL library.
+## AlphaAI-Chatty-INT2
+### Overview
+AlphaAI-Chatty-INT2 is a fine-tuned meta-llama/Llama-3.2-3B-Instruct model optimized for **empathic**, **chatty**, and **engaging** conversations. Building on the foundations of our INT1 release, the INT2 version includes enhanced conversational capabilities that make it more context-aware, responsive, and personable. Trained on an improved proprietary conversational dataset, this model is particularly suitable for local deployments requiring a **natural, interactive, and empathetic** dialogue experience.
+The model is available in GGUF format and has been quantized to different levels to support various hardware configurations.
+### Model Details
+- **Base Model:** meta-llama/Llama-3.2-3B-Instruct
+- **Fine-tuned By:** Alpha AI
+- **Training Framework:** Unsloth
+#### Quantization Levels Available
+- q4_k_m
+- q5_k_m
+- q8_0
+- 16-bit (this, full precision) - [Link](https://huggingface.co/alphaaico/AlphaAI-Chatty-INT2)
+*(Note: The INT1 16-bit link is referenced (https://huggingface.co/alphaaico/AlphaAI-Chatty-INT1)*
+**Format:** GGUF (Optimized for local deployments, https://huggingface.co/alphaaico/AlphaAI-Chatty-INT2-GGUF)
+### Use Cases
+- **Conversational AI** – Ideal for chatbots, virtual assistants, and customer support where empathetic and engaging interaction is crucial.
+- **Local AI Deployments** – Runs efficiently on local machines, negating the need for cloud-based inference.
+- **Research & Experimentation** – Suitable for studying advanced conversational AI techniques and fine-tuning on specialized or proprietary datasets.
+### Model Performance
+AlphaAI-Chatty-INT2 has been further optimized to deliver:
+- **Empathic and Context-Aware Responses** – Improved understanding of user inputs with a focus on empathetic replies.
+- **High Efficiency on Consumer Hardware** – Maintains quick inference speeds even with more advanced conversation modeling.
+- **Balanced Coherence and Creativity** – Strikes an ideal balance for real-world dialogue applications, allowing for both coherent answers and creative flair.
+### Limitations & Biases
+Like any AI system, this model may exhibit biases stemming from its training data. Users should employ it responsibly and consider additional fine-tuning if needed for sensitive or specialized applications.
+### License
+Released under the **Apache-2.0** license. For full details, please consult the license file in the Hugging Face repository.
+### Acknowledgments
+Special thanks to the Unsloth team for their optimized training pipeline for LLaMA models. Additional appreciation goes to Hugging Face’s TRL library for enabling accelerated and efficient fine-tuning workflows.