Downloads · 30 days
27
7% of all-time downloads
myrkur/shotor
shotor is a text generation model from myrkur. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
<a href="https://ibb.co/PwCN3VF"<img src="https://i.ibb.co/0hJc8zm/shotor.png" alt="shotor" border="0"</a
Downloads · 30 days
27
7% of all-time downloads
All-time downloads
391
Public
Parameters
8B
16.1 GB on disk
Likes
5
Public
Click a slice to open those files.
.safetensors16.1 GB · 100%
From the Hugging Face model README
<a href="https://ibb.co/PwCN3VF"><img src="https://i.ibb.co/0hJc8zm/shotor.png" alt="shotor" border="0"></a>
Shotor is a Persian language model built upon the llama 3 8B architecture, a multilingual Large Language Model (LLM). It has been fine-tuned using supervised learning techniques and the Dora method for efficient fine-tuning. The model has been specifically tailored and trained on Persian datasets, particularly leveraging the dataset provided by persian-alpaca-deep-clean.
Here's a sample Python code snippet demonstrating how to use Shotor for text generation:
import transformers
import torch
# Load the Shotor model
model_id = "myrkur/shotor"
pipeline = transformers.pipeline(
"text-generation",
model=model_id,
model_kwargs={"torch_dtype": torch.bfloat16},
device_map="auto",
)
# Define user messages
messages = [
{"role": "user", "content": "علم بهتر است یا ثروت؟"},
]
# Apply chat template and generate text
prompt = pipeline.tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
terminators = [
pipeline.tokenizer.eos_token_id,
pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
]
outputs = pipeline(
prompt,
max_new_tokens=512,
eos_token_id=terminators,
do_sample=True,
temperature=0.5,
top_p=0.9,
repetition_penalty=1.1
)
print(outputs[0]["generated_text"][len(prompt):])
Contributions to Shotor are welcome! Whether it's enhancing the model's capabilities, improving its performance on specific tasks, or evaluating its performance, your contributions can help advance Persian natural language processing.
For questions or further information, please contact: