What are the hardware requirements for Indic Gemma 2B Finetuned Sft Navarasa 2.0?

Indic Gemma 2B Finetuned Sft Navarasa 2.0 requires approximately 10 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Indic Gemma 2B Finetuned Sft Navarasa 2.0 and how large is it?

Indic Gemma 2B Finetuned Sft Navarasa 2.0 is developed by Telugu-LLM-Labs, a model with 2b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Indic Gemma 2B Finetuned Sft Navarasa 2.0 perform on standard benchmarks?

Indic Gemma 2B Finetuned Sft Navarasa 2.0 has the following published scores: MMLU 38.21. Compare against reference models on this page or on the LLM Explorer leaderboards.

Indic Gemma 2B Finetuned Sft Navarasa 2.0 by Telugu-LLM-Labs — VRAM 10GB, 8K context

Name: Indic Gemma 2B Finetuned Sft Navarasa 2.0
Author: Telugu-LLM-Labs

Indic Gemma 2B Finetuned Sft Navarasa 2.0 is an open-source language model by Telugu-LLM-Labs. Features: 2b LLM, VRAM: 10GB, Context: 8K, License: other, Fine-Tuned, Instruction-Based, LLM Explorer Score: 0.17, Arc: 44.7, HellaSwag: 68.4, MMLU: 38.2, GSM8K: 9.3.

As Base model:finetune:google/gem... Base model:google/gemma-2b Bn Dataset:abhinand/tamil-alpaca Dataset:hydraindiclm/bengali a... Dataset:hydraindiclm/punjabi a... Dataset:odiagenai/odia alpaca ... Dataset:ravithejads/samvaad-hi... Dataset:telugu-llm-labs/assame... Dataset:telugu-llm-labs/konkan... Dataset:telugu-llm-labs/marath... Dataset:telugu-llm-labs/nepali... Dataset:telugu-llm-labs/sindhi... Dataset:telugu-llm-labs/telugu... Dataset:telugu-llm-labs/telugu... Dataset:telugu-llm-labs/urdu a... Dataset:tensoic/airoboros-3.2 ... Dataset:tensoic/alpaca-gujarat... Dataset:tensoic/gpt-teacher kn Dataset:vishnupj/alpaca instru... Dataset:yahma/alpaca-cleaned En Endpoints compatible Finetuned Gemma Gu Hi Instruct Kn Ml Mr Ne Or Pa Region:us Safetensors Sd Sharded Ta Te Tensorflow Ur

Model Card on HF 🤗: https://huggingface.co/Telugu-LLM-Labs/Indic-gemma-2b-finetuned-sft-Navarasa-2.0

Indic Gemma 2B Finetuned Sft Navarasa 2.0 Parameters and Internals

Model Type

text generation

Additional Notes

The model can also be inferred using the HuggingFace Library or Unsloth library for faster inference.

Supported Languages

te (Telugu), en (English), ta (Tamil), ml (Malayalam), mr (Marathi), hi (Hindi), kn (Kannada), sd (Sindhi), ne (Nepali), ur (Urdu), as (Assamese), gu (Gujarati), bn (Bengali), pa (Punjabi), or (Odia)

Training Details

Data Sources:

ravithejads/samvaad-hi-filtered, Telugu-LLM-Labs/telugu_teknium_GPTeacher_general_instruct_filtered_romanized, Telugu-LLM-Labs/telugu_alpaca_yahma_cleaned_filtered_romanized, Telugu-LLM-Labs/sindhi_alpaca_yahma_cleaned_filtered, Telugu-LLM-Labs/urdu_alpaca_yahma_cleaned_filtered, Telugu-LLM-Labs/marathi_alpaca_yahma_cleaned_filtered, Telugu-LLM-Labs/assamese_alpaca_yahma_cleaned_filtered, Telugu-LLM-Labs/konkani_alpaca_yahma_cleaned_filtered, Telugu-LLM-Labs/nepali_alpaca_yahma_cleaned_filtered, abhinand/tamil-alpaca, Tensoic/airoboros-3.2_kn, Tensoic/gpt-teacher_kn, VishnuPJ/Alpaca_Instruct_Malayalam, Tensoic/Alpaca-Gujarati, HydraIndicLM/punjabi_alpaca_52K, HydraIndicLM/bengali_alpaca_dolly_67k, OdiaGenAI/Odia_Alpaca_instructions_52k, yahma/alpaca-cleaned

Data Volume:

approx 650K instruction samples

Methodology:

LoRA finetuning on instruction datasets

Context Length:

2048

Training Time:

45 Hours

Hardware Used:

1 A100, 80GB GPU

Input Output

Input Format:

### Instruction: {instruction} ### Input: {input} ## Response: {response}

LLM Name	Indic Gemma 2B Finetuned Sft Navarasa 2.0
Repository 🤗	https://huggingface.co/Telugu-LLM-Labs/Indic-gemma-2b-finetuned-sft-Navarasa-2.0
Base Model(s)	Gemma 2B google/gemma-2b
Model Size	2b
Required VRAM	10 GB
Updated	2026-08-06
Maintainer	Telugu-LLM-Labs
Model Type	gemma
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 0.1 GB: 3-of-3
Supported Languages	te en ta ml mr hi kn sd ne ur as gu bn pa or
Model Architecture	GemmaForCausalLM
License	other
Context Length	8192
Model Max Length	8192
Transformers Version	4.38.2
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	float32

Rank the Indic Gemma 2B Finetuned Sft Navarasa 2.0 capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Quantized Models of the Indic Gemma 2B Finetuned Sft Navarasa 2.0

Model	Likes	Downloads	VRAM
Gemma 2B Malayalam T2 Gguf	0	36	1 GB
...B Malayalam T2 Model Vllm 4bit	0	5	2 GB

Best Alternatives to Indic Gemma 2B Finetuned Sft Navarasa 2.0

Best Alternatives	Context / RAM	Downloads	Likes
Gita SastraGPT V1	8K / 5.1 GB	4	1
Pandas Tutor Gemma 2B	8K / 5.1 GB	6	1
...ma Code Instruct Finetune Test	8K / 5.1 GB	30	0
Gemma 2B Sft Preview	8K / 5 GB	13	0
Leniachat Gemma 2B V0	8K / 15.1 GB	57	14
...ma Instruct Finetune On Alpaca	8K / 5.1 GB	5	0
...ma Code Instruct Finetune Test	8K / 5.1 GB	10	0
Gemma 2B Persona Instruct	8K / 5.1 GB	5	0
...ma Code Instruct Finetune Test	8K / 5.1 GB	6	0
...ma Code Instruct Finetune Test	8K / 5.1 GB	9	0

Note: green Score (e.g. "73.2") means that the model is better than Telugu-LLM-Labs/Indic-gemma-2b-finetuned-sft-Navarasa-2.0.