PranavSharma10/LlamaFinetunedTest
PranavSharma10/LlamaFinetunedTest is an 8 billion parameter language model based on the Llama 3 architecture, fine-tuned using Llama-Factory. This model leverages unsloth/llama-3-8b-Instruct-bnb-4bit and meta-llama/Meta-Llama-3-8B-Instruct as its base, offering a context length of 8192 tokens. It is designed for general instruction-following tasks, providing a compact yet capable solution for various NLP applications.
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Model Overview
PranavSharma10/LlamaFinetunedTest is an 8 billion parameter instruction-tuned language model built upon the Llama 3 architecture. It was fine-tuned using the Llama-Factory framework, leveraging both unsloth/llama-3-8b-Instruct-bnb-4bit and meta-llama/Meta-Llama-3-8B-Instruct as its foundational models. This model is designed to handle a wide range of instruction-following tasks, making it suitable for various natural language processing applications.
Key Characteristics
- Base Architecture: Llama 3, providing a robust and well-established foundation.
- Parameter Count: 8 billion parameters, balancing performance with computational efficiency.
- Context Length: Supports an 8192-token context window, allowing for processing longer inputs and generating more coherent responses.
- Fine-tuning: Utilizes Llama-Factory for efficient and effective instruction-tuning.
Use Cases
This model is well-suited for applications requiring:
- General instruction following: Responding to prompts and performing tasks as instructed.
- Text generation: Creating coherent and contextually relevant text.
- Chatbots and conversational AI: Engaging in dialogue and providing informative responses.
- Prototyping and development: A capable base model for further specialization or integration into applications.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.