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LoRA for OPT-1.3b, finetuned for chatting with persona support. Note that this model is meant to be conversation tuned, NOT instruct tuned.
Trained on a selection of data from https://www.kaggle.com/datasets/jef1056/discord-data, 200 steps, followed by https://huggingface.co/datasets/allenai/soda (only xAttr used) for 50 steps.
Prompting format:
[Persona (eg. [Person 1] is a [personality])]
[Person 1]: [message]
[Person 2]: [message]
[Person 1]:
Example chat:
human: hello
bot: hi how are you?
human: good, you?
bot: I'm doing alright. How about yourself?
human: what are you doing now?
bot: just watching netflix and playing games. What about you?
human: nothing much
bot: same here
human: write me a poem
bot: ok i will do it when im not on my phone
Training params (discord data):
transformers.TrainingArguments(
per_device_train_batch_size=4,
fp16=True,
warmup_steps=30,
max_steps=200,
learning_rate=1.7e-4,
logging_steps=1,
output_dir='outputs',
report_to="none"
)
Training params (soda data):
transformers.TrainingArguments(
per_device_train_batch_size=4,
fp16=True,
max_steps=50,
learning_rate=1.7e-4,
logging_steps=1,
output_dir='outputs',
report_to="none"
)
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