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---
license: llama3
language:
- en
library_name: transformers
pipeline_tag: text2text-generation
---
**Model Name: llama_3_orca_mini_v4_8b**
# Llama-3-8b base model trained on Orca Style Mini Datasets
<img src="https://huggingface.co/pankajmathur/orca_mini_v4_8b/resolve/main/orca_minis_small.jpeg" width="auto" />
<strong>
Passionate about Generative AI? I help companies to privately train and deploy custom LLM/MLLM affordably. For startups, I can even assist with securing GPU grants to get you started. Let's chat!
<a href="https://www.linkedin.com/in/pankajam" target="_blank">https://www.linkedin.com/in/pankajam</a> Looking forward to connecting!
</strong>
<br>
### 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](https://github.com/EleutherAI/lm-evaluation-harness) from EleutherAI.
Here are the results on similar metrics used by [HuggingFaceH4 Open LLM Leaderboard](https://huggingface.co/spaces/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
```python
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](LICENSE)
**Quants**
GGUF : Coming Soon
AWQ: Coming Soon
|