lucyknada/

Neuronovo_neuronovo-9B-v0.4-exl2-6bpw

exl2 quant (measurement.json included)

original readme below

• Intel/orca_dpo_pairs
• mlabonne/chatml_dpo_pairs language:
• en library_name: transformers

1. Training Dataset: In addition to the Intel/orca_dpo_pairs dataset, this version incorporates a mlabonne/chatml_dpo_pairs. The combined datasets enhance the model's capabilities in dialogues and interactive scenarios, further specializing it in natural language understanding and response generation.
2. Tokenizer and Formatting: The tokenizer now originates directly from the Neuronovo/neuronovo-9B-v0.2 model.
3. Training Configuration: The training approach has shifted from using max_steps=200 to num_train_epochs=1. This represents a change in the training strategy, focusing on epoch-based training rather than a fixed number of steps.
4. Learning Rate: The learning rate has been reduced to a smaller value of 5e-8. This finer learning rate allows for more precise adjustments during the training process, potentially leading to better model performance.