🚀 Dorna-Llama3-8B-Instruct
The Dorna models are decoder-only models, fine - tuned on Persian data by Part AI. This release offers an 8B instruct model, built upon Meta Llama 3 Instruct.
🚀 Quick Start
You can run conversational inference using the Transformers Auto classes with the generate()
function.
✨ Features
- Family of decoder - only models.
- Specifically trained/fine - tuned on Persian data.
- Built using the Meta Llama 3 Instruct model.
📦 Installation
No installation steps are provided in the original document, so this section is skipped.
💻 Usage Examples
Basic Usage
import torch
import transformers
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(
model_path,
torch_dtype=torch.bfloat16,
device_map="auto",
)
messages = [
{"role": "system",
"content": "You are a helpful Persian assistant. Please answer questions in the asked language."},
{"role": "user", "content": "کاغذ A4 بزرگ تر است یا A5؟"},
]
input_ids = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
return_tensors="pt"
).to(model.device)
terminators = [
tokenizer.eos_token_id,
tokenizer.convert_tokens_to_ids("<|eot_id|>")
]
outputs = model.generate(
input_ids,
max_new_tokens=256,
eos_token_id=terminators,
do_sample=True,
temperature=0.6,
top_p=0.9,
)
response = outputs[0][input_ids.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True))
You can also use the notebook below to test the model in Google Colab.

📚 Documentation
Evaluation
This model is evaluated on various tasks, including Boolean Questions, Code Generation, etc. Both human evaluation and automatic evaluation (with GPT - 4 as the judge) are performed.
Human Evaluation
Overall human evaluation results:
Model Pairs |
Parameters |
Win % |
Lose % |
Tie % |
Dorna - 8B - it vs. Meta - Llama - 3 - 8B - Instruct |
8B |
36.94 |
17.39 |
45.67 |
Dorna - 8B - it vs. GPT 3.5 turbo - 1106 |
N.A. |
32.01 |
26.94 |
41.05 |
Dorna - 8B - it vs. Persian Mind |
7B |
55.77 |
10.49 |
33.74 |
Category - based human evaluation results:
Model Pairs |
Parameters |
Bool Complex |
Bool Easy |
Code Gen |
General Long Response |
Historical Long Response |
Math Complex |
Math Easy |
News QA Complex |
News QA Easy |
Paraphrasing |
General Knowledge Easy |
General Knowledge Hard |
Summarization |
Dorna - 8B - it vs. Meta - Llama - 3 - 8B - Instruct |
8B |
0.25/0.25/0.5 |
0.28/0.35/0.38 |
0.6/0.1/0.3 |
0.8/0.08/0.12 |
0.4/0.3/0.3 |
0.28/0.08/0.65 |
0.47/0.00/0.53 |
0.55/0.07/0.38 |
0.43/0.15/0.42 |
0.1/0.05/0.85 |
0.31/0.2/0.49 |
0.59/0.13/0.28 |
0.28/0.2/0.53 |
Dorna - 8B - it vs. GPT 3.5 turbo - 1106 |
N.A. |
0.35/0.35/0.3 |
0.3/0.3/0.4 |
0.1/0.3/.06 |
0.2/0.45/0.35 |
0.46/0.27/0.27 |
0.25/0.1/0.65 |
0.05/0.1/0.85 |
0.12/0.35/0.53 |
0.15/0.1/0.75 |
0.25/0.15/0.6 |
0.3/0.32/0.38 |
0.22/0.53/0.25 |
0.35/0.55/0.1 |
Dorna - 8B - it vs. Persian Mind |
7B |
0.47/0.25/0.28 |
0.57/0.15/0.28 |
0.9/0.1/0.0 |
0.82/0.08/0.1 |
0.4/0.17/0.42 |
0.3/0.0/0.7 |
0.22/0.08/0.7 |
0.72/0.07/0.2 |
0.7/0.0/0.3 |
0.7/0.05/0.25 |
0.51/0.12/0.37 |
0.61/0.1/0.29 |
0.93/0.0/0.07 |
Automatic Evaluation
Model Pairs |
Parameters |
Overall Win Rate % |
Easy Win Rate % |
Hard Win Rate % |
Dorna - 8B - it vs. Llama 3 base |
8B |
58.96 |
56.00 |
64.49 |
Dorna - 8B - it vs. Part Mistral |
7B |
77.20 |
73.00 |
85.05 |
Dorna - 8B - it vs. Persian Mind |
7B |
90.88 |
87.50 |
97.20 |
Dorna - 8B - it vs. Neuraorca Gemma 7b |
7B |
86.32 |
86.50 |
85.98 |
Dorna - 8B - it vs. Maral 7b |
7B |
97.39 |
97.00 |
98.13 |
Dorna - 8B - it vs. PersianLlama 7b |
7B |
98.70 |
98.00 |
100.00 |
Dorna - 8B - it vs. Aya - 23 - 8B |
8B |
52.77 |
56.50 |
45.79 |
Dorna - 8B - it vs. Aya - 23 - 35B |
35B |
45.93 |
54.00 |
30.84 |
Dorna - 8B - it vs. Command R |
35B |
58.63 |
61.00 |
54.21 |
🔧 Technical Details
No technical details are provided in the original document, so this section is skipped.
📄 License
The license of this model is llama3.
Contact us
If you have any questions regarding this model, you can reach us via the community on Hugging Face.