OrcaAgent-llama3.2-8b-GGUF
| Property | Value |
|---|---|
| Parameter Count | 8.03B |
| License | Apache 2.0 |
| Base Model | Isotonic/OrcaAgent-llama3.2-8b |
| Training Data | microsoft/orca-agentinstruct-1M-v1, Isotonic/agentinstruct-1Mv1-combined |
What is OrcaAgent-llama3.2-8b-GGUF?
OrcaAgent-llama3.2-8b-GGUF is a quantized version of the Llama 3.2 8B model, specifically trained on Orca agent instruction datasets. This model represents a significant advancement in making large language models more accessible through various quantization options, ranging from 3.3GB to 16.2GB in size.
Implementation Details
The model offers multiple quantization variants optimized for different use cases, with the most notable being Q4_K_S and Q4_K_M, which are recommended for their balance of speed and quality. The quantization options include specialized versions like Q8_0 for best quality and lighter versions like Q2_K for minimal storage requirements.
- Multiple quantization options (Q2_K through Q8_0)
- File sizes ranging from 3.3GB to 16.2GB
- Optimized for text-generation-inference
- Built on the Llama architecture
Core Capabilities
- Efficient text generation and inference
- Optimized for conversational AI applications
- Supports English language processing
- Compatible with transformers library
Frequently Asked Questions
Q: What makes this model unique?
The model's unique strength lies in its variety of quantization options, allowing users to choose between different speed-quality-size tradeoffs. The Q4_K_S and Q4_K_M variants are particularly notable for offering a good balance of performance and efficiency.
Q: What are the recommended use cases?
The model is well-suited for conversational AI applications, text generation tasks, and scenarios where efficient inference is required. The various quantization options make it adaptable to different hardware constraints and performance requirements.
