yahma/alpaca-cleaned
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How to use XeroCodes/xero-8b with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-7b-it-bnb-4bit")
model = PeftModel.from_pretrained(base_model, "XeroCodes/xero-8b")Xero-8B is a fine-tuned language model based on google/gemma-7b-it, optimized to excel as a conversational agent. This model has been fine-tuned on the yahma/alpaca-cleaned dataset to enhance its conversational abilities and comprehension, making it an excellent choice for applications requiring advanced dialogue capabilities and understanding.
Xero-8B builds upon the strong foundation of the Gemma-7B-Instruct model, enhancing its conversational skills and ability to understand and respond to complex queries. The fine-tuning process with the yahma/alpaca-cleaned dataset ensures that Xero-8B can handle diverse and intricate conversations with ease.