What are the hardware requirements for Lm 1.3B Select 30B Tokens By Perplexity Bottom K?

Lm 1.3B Select 30B Tokens By Perplexity Bottom K requires approximately 5.4 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Lm 1.3B Select 30B Tokens By Perplexity Bottom K and how large is it?

Lm 1.3B Select 30B Tokens By Perplexity Bottom K is developed by princeton-nlp, a model with 30b 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 Lm 1.3B Select 30B Tokens By Perplexity Bottom K?

Lm 1.3B Select 30B Tokens By Perplexity Bottom K is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Lm 1.3B Select 30B Tokens By Perplexity Bottom K by princeton-nlp — VRAM 5.4GB, 4K context

Name: Lm 1.3B Select 30B Tokens By Perplexity Bottom K
Author: princeton-nlp

Lm 1.3B Select 30B Tokens By Perplexity Bottom K is an open-source language model by princeton-nlp. Features: 30b LLM, VRAM: 5.4GB, Context: 4K, LLM Explorer Score: 0.13.

Endpoints compatible Llama Pytorch Region:us

Model Card on HF 🤗: https://huggingface.co/princeton-nlp/lm-1.3B-select_30B_tokens_by-perplexity-bottom_k

Lm 1.3B Select 30B Tokens By Perplexity Bottom K Parameters and Internals

LLM Name	Lm 1.3B Select 30B Tokens By Perplexity Bottom K
Repository 🤗	https://huggingface.co/princeton-nlp/lm-1.3B-select_30B_tokens_by-perplexity-bottom_k
Model Size	30b
Required VRAM	5.4 GB
Updated	2026-05-21
Maintainer	princeton-nlp
Model Type	llama
Model Files	5.4 GB
Model Architecture	LlamaForCausalLM
Context Length	4096
Model Max Length	4096
Transformers Version	4.34.0
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	float32

Rank the Lm 1.3B Select 30B Tokens By Perplexity Bottom K capabilities

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Note: green Score (e.g. "73.2") means that the model is better than princeton-nlp/lm-1.3B-select_30B_tokens_by-perplexity-bottom_k.