| --- |
| license: other |
| language: |
| - en |
| base_model: |
| - meta-llama/Llama-3.1-8B-Instruct |
| pipeline_tag: text-generation |
| tags: |
| - character |
| --- |
| # 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: |
| ```python |
| 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])) |
