from transformers import AutoTokenizer, AutoModelForCausalLM

# Load model and tokenizer
tokenizer = AutoTokenizer.from_pretrained("wxkkxw/microsoft_DialoGPT-small_databricks-dolly-15k_qlora")
model = AutoModelForCausalLM.from_pretrained("wxkkxw/microsoft_DialoGPT-small_databricks-dolly-15k_qlora")

# Generate text
prompt = "{example_prompt}"
inputs = tokenizer(prompt, return_tensors="pt")

outputs = model.generate(
    **inputs,
    max_new_tokens={max_new_tokens},
    temperature={temperature},
    top_p={top_p}
)

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

Limitations and Biases

{limitations_list}

Citation

bibtex

@misc{{{citation_key},
  author = {{{citation_authors}}},
  title = {{{citation_title}}},
  year = {{{citation_year}}},
  publisher = {{Hugging Face}},
  url = {{https://huggingface.co/wxkkxw/microsoft_DialoGPT-small_databricks-dolly-15k_qlora}}
}}

Model Card Authors

Mathhead

Model Card Contact

For questions and feedback, please contact: {contact_email}

This model card was generated from template on 2025-11-15.