RLM_hingu

RLM_hingu is a fine-tuned version of the Gemma-3B Instruct model, adapted for casual Hinglish (Hindi-English) conversation using the keras-nlp framework. It is designed for lightweight conversational tasks in Hinglish, optimized with the JAX backend for efficiency.

Model Overview

• Base model: gemma3_instruct_1b
• Library: keras-nlp
• Backend: JAX (recommended for best performance)
• Sampling Method: Top-K (k=10)
• Use Case: Conversational Hinglish response generation

Usage

from keras_nlp.models import Gemma3CausalLM
from keras_nlp.samplers import TopKSampler

model = Gemma3CausalLM.from_preset("hf://rudrashah/RLM_hingu")
template = "Question:\n{question}\n\nAnswer:\n{answer}"
prompt = template.format(
    question="Rudra acha ladka hai?",
    answer="",
)
output = model.generate(prompt, max_length=256)
print(output)

Question:
Rudra acha ladka hai?

Answer:
haan, sabse best hai.

To run RLM_hingu, just paste this code and wait.