What are the hardware requirements for Mlnp Project Base?

Mlnp Project Base requires approximately 0.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mlnp Project Base and how large is it?

Mlnp Project Base is developed by giewont, a model with 270m parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Mlnp Project Base?

Mlnp Project Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mlnp Project Base by giewont — VRAM 0.5GB

Name: Mlnp Project Base
Author: giewont

Mlnp Project Base is an open-source language model by giewont. Features: 270m LLM, VRAM: 0.5GB, Instruction-Based, LLM Explorer Score: 0.12.

Autotrain compatible Custom code Instruct Openelm Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/giewont/mlnp-project-base

Mlnp Project Base Parameters and Internals

LLM Name	Mlnp Project Base
Repository 🤗	https://huggingface.co/giewont/mlnp-project-base
Model Size	270m
Required VRAM	0.5 GB
Updated	2025-09-23
Maintainer	giewont
Model Type	openelm
Instruction-Based	Yes
Model Files	0.5 GB
Model Architecture	OpenELMForCausalLM
Transformers Version	4.41.0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Mlnp Project Base 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

Best Alternatives to Mlnp Project Base

Best Alternatives	Context / RAM	Downloads	Likes
OpenELM 270M Instruct	0K / 0.5 GB	1255	145
OpenELM 270M Instruct	0K / 1.1 GB	8	0
...enELM270M DPO FINAL PREFERENCE	0K / 0.5 GB	6	0
M2 Oelm270m	0K / 1.1 GB	9	0
...M 270M Instruct With Tokenizer	0K / 0.5 GB	6	0
Taiwan ELM 270M Instruct	0K / 1.2 GB	16	1

Note: green Score (e.g. "73.2") means that the model is better than giewont/mlnp-project-base.