What are the hardware requirements for Pythia 14M Finewebedu Sentences?

Pythia 14M Finewebedu Sentences requires approximately 0.1 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Pythia 14M Finewebedu Sentences and how large is it?

Pythia 14M Finewebedu Sentences is developed by agentlans, a model with 14m 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 Pythia 14M Finewebedu Sentences?

Pythia 14M Finewebedu Sentences is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Pythia 14M Finewebedu Sentences by agentlans — VRAM 0.1GB, 2K context

Name: Pythia 14M Finewebedu Sentences
Author: agentlans

Pythia 14M Finewebedu Sentences is an open-source language model by agentlans. Features: 14m LLM, VRAM: 0.1GB, Context: 2K, LLM Explorer Score: 0.14.

Autotrain compatible Base model:eleutherai/pythia-1... Base model:finetune:eleutherai... Endpoints compatible Generated from trainer Gpt neox Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/agentlans/pythia-14m-finewebedu-sentences

Pythia 14M Finewebedu Sentences Parameters and Internals

Model Type

text generation

Use Cases

Primary Use Cases:

Generating short lines of English text

Limitations:

Not guaranteed to make sensible, coherent, or grammatically correct sentences, No regard for accuracy or truthfulness whatsoever

Training Details

Data Sources:

agentlans/finewebedu-sentences

LLM Name	Pythia 14M Finewebedu Sentences
Repository 🤗	https://huggingface.co/agentlans/pythia-14m-finewebedu-sentences
Base Model(s)	Pythia 14M EleutherAI/pythia-14m
Model Size	14m
Required VRAM	0.1 GB
Updated	2025-09-23
Maintainer	agentlans
Model Type	gpt_neox
Model Files	0.1 GB
Model Architecture	GPTNeoXForCausalLM
Context Length	2048
Model Max Length	2048
Transformers Version	4.44.2
Tokenizer Class	GPTNeoXTokenizer
Vocabulary Size	50304
Torch Data Type	float32

Rank the Pythia 14M Finewebedu Sentences capabilities

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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

Best Alternatives to Pythia 14M Finewebedu Sentences

Best Alternatives	Context / RAM	Downloads	Likes
Pythia 14M	2K / 0 GB	239461	6
Pythia 14m Sft	2K / 0.1 GB	5	0
...t Llm Pythia 14M Pm Gen Ian Nd	2K / 0.1 GB	6	0
SmallLM	2K / 0 GB	38	1
Pythia 14M	2K / 0 GB	7	0
Tinyllama Random	2K / 0.1 GB	7	0

Note: green Score (e.g. "73.2") means that the model is better than agentlans/pythia-14m-finewebedu-sentences.