knowrohit07/know-doctor
The knowrohit07/know-doctor is a 7 billion parameter language model. This model was trained using bitsandbytes 4-bit quantization with nf4 quantization type and double quantization enabled, utilizing bfloat16 compute dtype. It is designed for general language tasks, with specific training details indicating a focus on efficient deployment.
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Model Overview
The knowrohit07/know-doctor is a 7 billion parameter language model. While specific details regarding its architecture, training data, and primary use cases are marked as "More Information Needed" in its model card, the training procedure indicates a focus on efficient quantization for deployment.
Key Training Details
This model was trained using the bitsandbytes library with the following quantization configuration:
- Quantization Method: bitsandbytes
- Load in 4-bit: True
- Quantization Type: nf4 (NormalFloat 4-bit)
- Double Quantization: Enabled (
bnb_4bit_use_double_quant: True) - Compute Dtype: bfloat16
This configuration suggests an optimization for reduced memory footprint and potentially faster inference, making it suitable for environments with limited resources.
Current Limitations
As per the provided model card, significant information is currently unavailable, including:
- Model type and language(s)
- Specific use cases (direct or downstream)
- Bias, risks, and limitations
- Training data and evaluation results
Users should exercise caution and conduct their own evaluations before deploying this model for critical applications, given the lack of detailed documentation.