ollama quantize model to fp16

Full Example Code

import ollama

# Load the model
model_path = 'path/to/model.pt'
model = ollama.load_model(model_path)

# Create a QuantizationConfig
quant_config = ollama.QuantizationConfig(
    precision=ollama.Precision.FP16,
    weights_bits=8,
    activation_bits=8,
    batch_size=1  # adjust according to your model's requirements
)

# Initialize the Quantizer
quantizer = ollama.Quantizer(model, quant_config)

# Run Quantization
quantizer.run_quantization()

# Save the quantized model
model_path = 'path/to/model_fp16.pt'
ollama.save_model(model, model_path)

This code will load a trained neural network model, create a QuantizationConfig object to specify the FP16 settings, initialize the Quantizer, run the quantization process, and finally save the quantized model in FP16 format.

 ./llama-quantize --help  
 #  from llamal.cpp

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