metadata
license: apache-2.0
Model Description
Master is a collection of LLMs trained using human-collected seed questions and regenerate the answers with a mixture of high performance Open-source LLMs.
Master-Yi-9B is trained using the ORPO techniques. The model shows strong abilities in reasoning on coding and math questions.
Prompt Template
<|im_start|>system
You are a helpful AI assistant.<|im_end|>
<|im_start|>user
What is the meaning of life?<|im_end|>
<|im_start|>assistant
Examples
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
device = "cuda" # the device to load the model onto
model = AutoModelForCausalLM.from_pretrained(
"vilm/VinaLlama2-14B",
torch_dtype='auto',
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("vilm/VinaLlama2-14B")
prompt = "What is the mearning of life?"
messages = [
{"role": "system", "content": "You are a helpful AI assistant."},
{"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(device)
generated_ids = model.generate(
model_inputs.input_ids,
max_new_tokens=1024,
eos_token_id=tokenizer.eos_token_id,
temperature=0.25,
)
generated_ids = [
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]
response = tokenizer.batch_decode(generated_ids)[0]
print(response)