What are the hardware requirements for Gptnoise37?

Gptnoise37 requires approximately 13.5 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gptnoise37 and how large is it?

Gptnoise37 is developed by visdata, a model with 6.7b 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 Gptnoise37?

Gptnoise37 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gptnoise37 by visdata — VRAM 13.5GB, 128K context

Name: Gptnoise37
Author: visdata

Gptnoise37 is an open-source language model by visdata. Features: 6.7b LLM, VRAM: 13.5GB, Context: 128K, LLM Explorer Score: 0.15.

Arxiv:1910.09700 Autotrain compatible Conversational Endpoints compatible Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/visdata/gptnoise37

Gptnoise37 Parameters and Internals

LLM Name	Gptnoise37
Repository 🤗	https://huggingface.co/visdata/gptnoise37
Model Size	6.7b
Required VRAM	13.5 GB
Updated	2024-11-27
Maintainer	visdata
Model Type	llama
Model Files	5.0 GB: 1-of-3 5.0 GB: 2-of-3 3.5 GB: 3-of-3
Model Architecture	LlamaForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.45.1
Tokenizer Class	GPT2Tokenizer
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Gptnoise37 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 Gptnoise37

Best Alternatives	Context / RAM	Downloads	Likes
...Deepseek Coder 6.7B Energy Sft	16K / 13.5 GB	261	0
Deepseek Coder 6.7B Base	16K / 13.5 GB	54216	124
Speechless Coder Ds 6.7B	16K / 13.5 GB	459	7
OpenCodeInterpreter DS 6.7B	16K / 13.5 GB	20040	135
...s Coder6.7b Reflct Adamw Iter2	16K / 13.5 GB	480	0
...ir8 Ds Coder6.7b Rmsprop Iter4	16K / 13.5 GB	183	0
...s Coder6.7b Reflct Adamw Iter1	16K / 13.5 GB	475	0
...ir8 Ds Coder6.7b Rmsprop Iter2	16K / 13.5 GB	183	0
...ir8 Ds Coder6.7b Rmsprop Iter3	16K / 13.5 GB	165	0
...s Coder6.7b Reflct Adamw Iter3	16K / 13.5 GB	430	0

Note: green Score (e.g. "73.2") means that the model is better than visdata/gptnoise37.