Model Name: llama_3_orca_mini_v5_8b_dpo
llama_3_orca_mini_v5_8b trained with various DPO Datasets
![](https://huggingface.co/pankajmathur/orca_mini_v5_8b/resolve/main/orca_minis_small.jpeg)
NOTICE
By providing proper credit and attribution, you are granted permission to use this model as a foundational base for further Full fine tuning, DPO, PPO or ORPO tuning and any kind of Merges. I actively encourage users to customize and enhance the model according to their specific needs, as this version is designed to be a comprehensive general model. Dive in and innovate!
Evaluation
Metric | Value |
---|---|
Avg. | 67.78 |
AI2 Reasoning Challenge (25-Shot) | 61.86 |
HellaSwag (10-Shot) | 82.35 |
MMLU (5-Shot) | 65.10 |
TruthfulQA (0-shot) | 56.24 |
Winogrande (5-shot) | 73.40 |
GSM8k (5-shot) | 67.70 |
Example Usage
Here is the ChatML prompt format
<|im_start|>system
You are Orca Mini, a helpful AI assistant.<|im_end|>
<|im_start|>user
Hello Orca Mini, what can you do for me?<|im_end|>
<|im_start|>assistant
Below shows a code example on how to use this model
from transformers import AutoModel, AutoTokenizer
model_slug = "pankajmathur/orca_mini_v5_8b_dpo"
model = AutoModel.from_pretrained(model_slug)
tokenizer = AutoTokenizer.from_pretrained(model_slug)
messages = [
{"role": "system", "content": "You are Orca Mini, a helpful AI assistant."},
{"role": "user", "content": "Hello Orca Mini, what can you do for me?"}
]
gen_input = tokenizer.apply_chat_template(messages, return_tensors="pt")
model.generate(**gen_input)
This model is governed by META LLAMA 3 COMMUNITY LICENSE AGREEMENT
Quants
GGUF : Coming Soon
AWQ: Coming Soon
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