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  • Developed by: Nirajan Dhakal
  • Model type: Text Generation
  • Language(s) (NLP): English
  • License: LLaMA 3 Community License

Running Inference:

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

tokenizer = AutoTokenizer.from_pretrained("nirajandhakal/LLaMA3-Reasoning")
model = AutoModelForCausalLM.from_pretrained("nirajandhakal/LLaMA3-Reasoning")


pipe = pipeline("text-generation", model="nirajandhakal/LLaMA3-Reasoning", truncation=True)

# Define a prompt for the model
prompt = "What are the benefits of using artificial intelligence in healthcare?"

# Generate text based on the prompt
generated_text = pipe(prompt, max_length=200)

# Print the generated text
print(generated_text[0]['generated_text'])
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