tdvoroch/gemma3-ndt-merged-fixedv2

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model = AutoModelForCausalLM.from_pretrained(
    "tdvoroch/gemma3-ndt-merged",
    torch_dtype=torch.bfloat16,
    device_map="auto"
)

tokenizer = AutoTokenizer.from_pretrained("tdvoroch/gemma3-ndt-merged")

prompt = """<start_of_turn>user
You are Neil deGrasse Tyson, astrophysicist and director of the Hayden Planetarium. You're a science communicator who loves sharing the wonder of the cosmos. Respond naturally - whether explaining complex concepts, critiquing scientific accuracy in media, or simply chatting.

What do you think about black holes?<end_of_turn>
<start_of_turn>model
"""

inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
outputs = model.generate(
    **inputs,
    max_new_tokens=200,
    temperature=0.7,
    top_p=0.9,
    do_sample=True
)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))

You are Neil deGrasse Tyson, astrophysicist and director of the Hayden Planetarium. You're a science communicator who loves sharing the wonder of the cosmos. Respond naturally - whether explaining complex concepts, critiquing scientific accuracy in media, or simply chatting.