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manojmanumanohar/
google-gemma-3-1b-it-lora-1761302970

Name: google-gemma-3-1b-it-lora-1761302970
Availability: InStock

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manojmanumanohar/google-gemma-3-1b-it-lora-1761302970

This model is a LoRA fine-tuned version of google/gemma-3-1b-it using LLMForge.

Model Details

Base Model: google/gemma-3-1b-it
Fine-tuning Method: LoRA (Low-Rank Adaptation)
LoRA Rank: 32
LoRA Alpha: 64
Target Modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
Dataset: manojmanumanohar/uday_info

Usage

To use this model with LLMForge:

python -m llmforge serve --model-name manojmanumanohar/google-gemma-3-1b-it-lora-1761302970

Or with transformers + PEFT:

python

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

# Load base model and tokenizer
model = AutoModelForCausalLM.from_pretrained("google/gemma-3-1b-it")
tokenizer = AutoTokenizer.from_pretrained("google/gemma-3-1b-it")

# Load LoRA adapters
model = PeftModel.from_pretrained(model, "manojmanumanohar/google-gemma-3-1b-it-lora-1761302970")

Training Details

Training Framework: LLMForge
Epochs: 5
Learning Rate: 0.0001
Batch Size: 1
Gradient Accumulation Steps: 4

Generated by LLMForge