Qwen2.5-72B-Instruct

Description

Qwen2.5-72B-Instruct is a large language model designed for instruction following and general-purpose text generation. It is part of the Qwen2.5 series, featuring 72 billion parameters and optimized for conversational AI and task completion.

Intended use

This model is intended for:

• General question answering
• Text generation and completion
• Conversational AI applications
• Instruction following tasks
• Content creation and summarization

Limitations

• May produce incorrect or misleading information
• Performance may vary across different domains and languages
• Should not be used for critical decision-making without human oversight
• May reflect biases present in training data

How to use

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "Jiaao/Qwen2.5-72B-Instruct"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

prompt = "Hello, how can I help you today?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Or using the chat template:

messages = [
    {"role": "user", "content": "Hello!"}
]
text = tokenizer.apply_chat_template(messages, tokenize=False)