SydneyBot - LLaMA 8B Model (v1)

Model Description

This is a fine-tuned version of the LLaMA 8B model, trained to emulate the personality of a fictional character named Sydney. The model is trained for conversational AI and supports text generation tasks.

• Architecture: LLaMA 8B
• Fine-tuned On: Custom dataset representing the personality of Sydney
• Size: 8B parameters
• Task: Text generation (Causal Language Modeling)

Intended Use

• Primary Use: This model is intended for text generation, including role-playing chat, dialogue systems, and storytelling.
• How to Use: The model can be used via the Hugging Face Inference API or integrated into custom applications using transformers.

Example Usage:

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("Eschatol/SydneyBot")
tokenizer = AutoTokenizer.from_pretrained("Eschatol/SydneyBot")

inputs = tokenizer("Hello, Sydney!", return_tensors="pt")
outputs = model.generate(inputs["input_ids"], max_length=50)
print(tokenizer.decode(outputs[0]))