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Open-weight model

ppt-pythia-160m-uniform250-previous_mse_delta_shuffle1-seed1024-stage2

by Qing Yao qing-yao/ppt-pythia-160m-uniform250-previous_mse_delta_shuffle1-seed1024-stage2

ppt-pythia-160m-uniform250-previous_mse_delta_shuffle1-seed1024-stage2 is an open-weight model from Qing Yao. It has 162M parameters and a 2,048-token context. At 16-bit it needs about 0.4 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.

Parameters162M
Context2,048
Weights2.3 GB
License—
AccessOpen weights
Monthly Downloads—

Runs On

What it takes to serve ppt-pythia-160m-uniform250-previous_mse_delta_shuffle1-seed1024-stage2 (162M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

PrecisionWeightsMemory neededCheapest setupPer hourAlso fits
16-bit 0.3 GB 0.4 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 0.2 GB 0.2 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 0.1 GB 0.1 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Oct 19, 2026.

ppt-pythia-160m-uniform250-previous_mse_delta_shuffle1-seed1024-stage2 on every accelerator the SAVRN Index prices, at every precision

Model Card

The publisher has not written a card for this model.

Configuration

Architecture
GPTNeoXForCausalLM
Context length (tokens)
2,048
Layers
12
Hidden size
768
Feed-forward size
3,072
Attention heads
12
Vocabulary size
50,304
Model type
gpt_neox

Identity and Version

Repository
qing-yao/ppt-pythia-160m-uniform250-previous_mse_delta_shuffle1-seed1024-stage2
Publisher
Qing Yao
Task
Not stated by the source
Modality
Other
Library
Not stated by the source
Parameters
162M parameters
Languages
Not stated by the source
Revision
272e0b98c14ac8229bdc33e5bcf363dc4ba48573
First published
2026-09-26
Last updated
2026-09-26

Files and Weights

29 files, 2.3 GB in total. The weights are 12 files totalling 2.3 GB in bin, pt, pth, safetensors.

Weights12 files · 2.3 GB
Configuration10 files · 120.4 KB
Tokenizer6 files · 10.7 MB
Repository1 file · 1.5 KB
Every file
FileTypeSizeSHA-256
checkpoint-2000/model.safetensorsWeights324.7 MB a05df2dfd3b7
checkpoint-2000/optimizer.ptWeights649.4 MB edc9ecc9bb8a
checkpoint-2000/rng_state.pthWeights14.6 KB 276504d728eb
checkpoint-2000/scheduler.ptWeights1.5 KB 70a8cd55d7a2
checkpoint-2000/training_args.binWeights5.4 KB 302999177336
checkpoint-4000/model.safetensorsWeights324.7 MB 3ce3a530d5c8
checkpoint-4000/optimizer.ptWeights649.4 MB 15cc9aff1300
checkpoint-4000/rng_state.pthWeights14.6 KB c5a3cb7f15e7
checkpoint-4000/scheduler.ptWeights1.5 KB 59828c1e7072
checkpoint-4000/training_args.binWeights5.4 KB 302999177336
model.safetensorsWeights324.7 MB 3ce3a530d5c8
training_args.binWeights5.4 KB 302999177336
checkpoint-2000/config.jsonConfiguration781 B —
checkpoint-2000/generation_config.jsonConfiguration225 B —
checkpoint-2000/trainer_state.jsonConfiguration15.4 KB —
checkpoint-4000/config.jsonConfiguration781 B —
checkpoint-4000/generation_config.jsonConfiguration225 B —
checkpoint-4000/trainer_state.jsonConfiguration30.1 KB —
config.jsonConfiguration781 B —
experiment.jsonConfiguration41.8 KB —
generation_config.jsonConfiguration225 B —
trainer_state.jsonConfiguration30.1 KB —
.gitattributesRepository1.5 KB —
checkpoint-2000/tokenizer.jsonTokenizer3.6 MB —
checkpoint-2000/tokenizer_config.jsonTokenizer349 B —
checkpoint-4000/tokenizer.jsonTokenizer3.6 MB —
checkpoint-4000/tokenizer_config.jsonTokenizer349 B —
tokenizer.jsonTokenizer3.6 MB —
tokenizer_config.jsonTokenizer349 B —

License and Download

License
Not stated by the source
Access
Open weights, no gate
Download size
2.3 GB
Download from Qing Yao

Released by Qing Yao through its official repository on Hugging Face.

Memory Requirements

PrecisionWeights in memory
As published2.3 GB
16-bit0.3 GB
8-bit0.2 GB
4-bit0.1 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About ppt-pythia-160m-uniform250-previous_mse_delta_shuffle1-seed1024-stage2

How much GPU memory does ppt-pythia-160m-uniform250-previous_mse_delta_shuffle1-seed1024-stage2 need?

About 0.4 GB at 16-bit and 0.1 GB at 4-bit: the weights (162M parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run ppt-pythia-160m-uniform250-previous_mse_delta_shuffle1-seed1024-stage2 on?

At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

What is ppt-pythia-160m-uniform250-previous_mse_delta_shuffle1-seed1024-stage2's context length?

2,048 tokens, from the maximum position embeddings in its published configuration.