Question 1

What is QwQ-32B?

Accepted Answer

Introducing **Qwen/QwQ-32B**, a cutting-edge reasoning model designed to enhance your AI experience. This model stands out with its ability to think and reason, making it a powerful tool for tackling complex tasks.

Question 2

What are the features of QwQ-32B?

Accepted Answer

* **Type**: Causal Language Models
* **Architecture**: Transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias
* **Parameters**: 32.5 billion total, with 31 billion non-embedding
* **Layers**: 64
* **Attention Heads**: 40 for Q and 8 for KV
* **Context Length**: Full 131,072 tokens

Question 3

What are the use cases of QwQ-32B?

Accepted Answer

* **Text Generation**: Create engaging and coherent text for various applications.
* **Conversational AI**: Power chatbots and virtual assistants with advanced reasoning capabilities.
* **Complex Problem Solving**: Tackle challenging questions and tasks with ease.

Question 4

How to use QwQ-32B?

Accepted Answer

To get started, load the model and tokenizer using the following code snippet:

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "Qwen/QwQ-32B"

model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype="auto",
    device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(model_name)

prompt = "How many r's are in the word \"strawberry\""
messages = [
    {"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)

model_inputs = tokenizer([text], return_tensors="pt").to(model.device)

generated_ids = model.generate(
    **model_inputs,
    max_new_tokens=32768
)
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, skip_special_tokens=True)[0]
print(response)
```

Question 5

What is Qwen/QwQ-32B?

Accepted Answer

It is a reasoning model that excels in complex tasks and text generation.

Question 6

How many parameters does it have?

Accepted Answer

The model has 32.5 billion parameters.

Question 7

What are the recommended settings for optimal performance?

Accepted Answer

Use Temperature=0.6, TopP=0.95, and TopK between 20 and 40.