CJ-gyuwonpark/ch-70b-v9
CJ-gyuwonpark/ch-70b-v9 is a large language model developed by CJ-gyuwonpark. This model was trained using bitsandbytes 4-bit quantization with nf4 quantization type and double quantization enabled, utilizing bfloat16 compute dtype. Specific details regarding its architecture, parameter count, and primary use cases are not provided in the available documentation, but its training configuration suggests an optimization for efficient deployment and inference.
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Model Overview
This model, CJ-gyuwonpark/ch-70b-v9, is a language model developed by CJ-gyuwonpark. While specific details on its architecture, parameter count, and core capabilities are not provided in the available documentation, its training procedure highlights a focus on efficient quantization.
Training Details
The model was trained using bitsandbytes 4-bit quantization. Key aspects of its training configuration include:
- Quantization Method:
bitsandbytes - Quantization Type:
nf4(NormalFloat 4-bit) - Double Quantization: Enabled (
bnb_4bit_use_double_quant: True) - Compute Dtype:
bfloat16 - Framework: PEFT 0.6.0.dev0
This quantization approach suggests an emphasis on reducing memory footprint and potentially speeding up inference, making it suitable for environments with resource constraints. Further information regarding its specific applications, performance benchmarks, and intended use cases is not available in the current model card.