What are the hardware requirements for Kaggle Llm 124M Base?

Kaggle Llm 124M Base requires approximately 0.2 GB of VRAM and supports a context window of 1K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Kaggle Llm 124M Base and how large is it?

Kaggle Llm 124M Base is developed by somdevsheel, a model with 124m 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 Kaggle Llm 124M Base?

Kaggle Llm 124M Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Kaggle Llm 124M Base by somdevsheel — VRAM 0.2GB, 1K context

Name: Kaggle Llm 124M Base
Author: somdevsheel

Kaggle Llm 124M Base is an open-source language model by somdevsheel. Features: 124m LLM, VRAM: 0.2GB, Context: 1K, License: apache-2.0, LLM Explorer Score: 0.33.

Dataset:huggingfacefw/fineweb-... En Endpoints compatible From-scratch Llama Region:us Safetensors Small-language-model

Model Card on HF 🤗: https://huggingface.co/somdevsheel/kaggle-llm-124m-base

Kaggle Llm 124M Base Parameters and Internals

LLM Name	Kaggle Llm 124M Base
Repository 🤗	https://huggingface.co/somdevsheel/kaggle-llm-124m-base
Model Size	124m
Required VRAM	0.2 GB
Updated	2026-11-11
Maintainer	somdevsheel
Model Type	llama
Model Files	0.2 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	1024
Model Max Length	1024
Transformers Version	4.41.2
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	50304
Torch Data Type	float16

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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

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