Model Name: llama_3_orca_mini_v4_8b
Llama-3-8b base model trained on Orca Style Mini Datasets
NOTICE
By providing proper credit and attribution, you are granted permission to use this model as a foundational base for further DPO/PPO tuning or 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, fully fine-tuned general model. Dive in and innovate!
Evaluation
We evaluated this model on a wide range of tasks using Language Model Evaluation Harness from EleutherAI.
Here are the results on similar metrics used by HuggingFaceH4 Open LLM Leaderboard
| Metric | Value |
|---|---|
| Avg. | 66.65 |
| AI2 Reasoning Challenge (25-Shot) | 58.02 |
| HellaSwag (10-Shot) | 81.65 |
| MMLU (5-Shot) | 63.23 |
| TruthfulQA (0-shot) | 55.78 |
| Winogrande (5-shot) | 73.95 |
| GSM8k (5-shot) | 67.25 |
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_v4_8b"
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