Dragneel/Phi-3-mini-Nepali-Text-Summarization-f16

Uploaded model

• —Developed by: Dragneel
• —License: apache-2.0
• —Finetuned from model : unsloth/Phi-3-mini-4k-instruct-bnb-4bit

Use The Model

from transformers import AutoTokenizer, AutoModelForCausalLM

Load the tokenizer and model

tokenizer = AutoTokenizer.from_pretrained("Dragneel/Phi-3-mini-Nepali-Text-Summarization-f16")

model = AutoModelForCausalLM.from_pretrained("Dragneel/Phi-3-mini-Nepali-Text-Summarization-f16")

Example input text

input_text = "Summarize Nepali Text in Nepali: काठमाडौंको बहिराव बसपार्कमा एक भयानक दुर्घटना घटेको थियो। रातको समय थियो र भारी बर्फ जम्मा भएको थियो।"

Tokenize the input text

inputids = tokenizer.encode(inputtext, return_tensors='pt')

Generate text with adjusted parameters

outputs = model.generate(inputids, maxnew_tokens=50)

Decode the generated tokens

generatedtext = tokenizer.decode(outputs[0], skipspecial_tokens=True)

print(generated_text)