qwen35_3.5m_dclm100m

kurogane/qwen35_3.5m_dclm100m

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_id = "kurogane/qwen35_3.5m_dclm100m"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id, 
    torch_dtype=torch.float16,
    device_map="auto",
    )

prompt = "hello!"

with torch.no_grad():
    token_ids = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt")
    output_ids = model.generate(
        token_ids.to(model.device),
        max_new_tokens=128,
        repetition_penalty=1.3,
        use_cache=False,
    )
output = tokenizer.decode(output_ids.tolist()[0][token_ids.size(1) :], skip_special_tokens=True)
print(output)

It is a subsidian program.

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