Andyrasika/mistral_autotrain_llm

Model Trained Using AutoTrain

from transformers import AutoModelForCausalLM, AutoTokenizer

model_path = "Andyrasika/mistral_autotrain_llm"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(model_path)

input_text = "Health benefits of regular exercise"
input_ids = tokenizer.encode(input_text, return_tensors="pt")
output = model.generate(input_ids)
predicted_text = tokenizer.decode(output[0], skip_special_tokens=False)
print(predicted_text)

Output:

Health benefits of regular exercise include improved cardiovascular health, increased strength and flexibility, improved mental

Resources:

• https://github.com/huggingface/autotrain-advanced/issues/339
• https://www.kdnuggets.com/how-to-use-hugging-face-autotrain-to-finetune-llms
• https://github.com/hiyouga/LLaMA-Factory#llama-factory-training-and-evaluating-large-language-models-with-minimal-effort