What are the hardware requirements for PrathameshLLM 2B?

PrathameshLLM 2B requires approximately 5.1 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 PrathameshLLM 2B and how large is it?

PrathameshLLM 2B is developed by pmking27, 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 PrathameshLLM 2B perform on standard benchmarks?

PrathameshLLM 2B has the following published scores: MMLU 38.21. Compare against reference models on this page or on the LLM Explorer leaderboards.

PrathameshLLM 2B by pmking27 — VRAM 5.1GB, 8K context

Name: PrathameshLLM 2B
Author: pmking27

PrathameshLLM 2B is an open-source language model by pmking27. Features: 2b LLM, VRAM: 5.1GB, Context: 8K, License: apache-2.0, LLM Explorer Score: 0.15, Arc: 44.7, HellaSwag: 68.4, MMLU: 38.2, GSM8K: 9.3.

As Base model:finetune:google/gem... Base model:google/gemma-2b Bn En Endpoints compatible Gemma Gu Hi Kn Ml Mr Ne Or Pa Region:us Safetensors Sd Sharded Ta Te Tensorflow Trl Unsloth Ur

Model Card on HF 🤗: https://huggingface.co/pmking27/PrathameshLLM-2B

PrathameshLLM 2B Parameters and Internals

Model Type

text-generation

Supported Languages

en (native), mr (native), hi (native), gu (native), pa (native), te (native), ta (native), ml (native), kn (native), sd (native), ne (native), ur (native), as (native), bn (native), or (native)

Training Details

Methodology:

The model was trained 2x faster using Unsloth and Huggingface's TRL library.

Input Output

Input Format:

Strings formatted with Alpaca prompt template.

Accepted Modalities:

text

Output Format:

Text response extracted from decoded output.

LLM Name	PrathameshLLM 2B
Repository 🤗	https://huggingface.co/pmking27/PrathameshLLM-2B
Base Model(s)	Gemma 2B google/gemma-2b
Model Size	2b
Required VRAM	5.1 GB
Updated	2026-07-27
Maintainer	pmking27
Model Type	gemma
Model Files	5.0 GB: 1-of-2 0.1 GB: 2-of-2
Supported Languages	en mr hi gu pa te ta ml kn sd ne ur as bn or
Model Architecture	GemmaForCausalLM
License	apache-2.0
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 PrathameshLLM 2B 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 PrathameshLLM 2B

Model	Likes	Downloads	VRAM
PrathameshLLM 2B GGUF	1	788	1 GB

Best Alternatives to PrathameshLLM 2B

Best Alternatives	Context / RAM	Downloads	Likes
Gemma 1.1 2B It	8K / 5.1 GB	209209	173
Gemma 2B It	8K / 5 GB	16802	3
Gemma 1.1 2B It	8K / 5 GB	43	3
Gemma 2B It Peru Legal Es V2	8K / 5.1 GB	8	1
Codegemma 2B	8K / 5.1 GB	33091	101
Gita SastraGPT V1	8K / 5.1 GB	4	1
Caca Tinny 2B V3	8K / 5.1 GB	4	1
Pandas Tutor Gemma 2B	8K / 5.1 GB	6	1
Gemma Qlora Customer Support	8K / 5.1 GB	8	0
... 2B Finetuned Sft Navarasa 2.0	8K / 10 GB	536	27

Note: green Score (e.g. "73.2") means that the model is better than pmking27/PrathameshLLM-2B.