# led-large-16384-BASE…ASPRPreACE3ep by Rosa Rodriguez-Sánchez
Source: https://savrn.com/models/led-large-16384-base3ep-asprpreace3ep
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

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## Runs On

What it takes to serve led-large-16384-BASE3ep-ASPRPreACE3ep (460M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
| --- | --- | --- | --- | --- | --- |
| 16-bit | 0.9 GB | 1.1 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |
| 8-bit | 0.5 GB | 0.6 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |
| 4-bit | 0.2 GB | 0.3 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/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](https://savrn.com/ai-index/pricing/gpus), read Oct 8, 2026.

[led-large-16384-BASE3ep-ASPRPreACE3ep on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/led-large-16384-base3ep-asprpreace3ep/gpus)

## Model Card

By Rosa Rodriguez-Sánchez, published under apache-2.0, revision 90f199862c6c.

This model is a fine-tuned version of [rosadecsai/led-large-16384-BASE3ep](https://huggingface.co/rosadecsai/led-large-16384-BASE3ep) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.0896 - Rouge1: 46.0449 - Rouge2: 15.3846 - Rougel: 20.0708 - Rougelsum: 44.1558 - Gen Len: 1.0

### Model description

More information needed

### Intended uses & limitations

More information needed

### Training and evaluation data

More information needed

### Training procedure

#### Training hyperparameters

The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 3 - mixed_precision_training: Native AMP

#### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 2.305 | 1.0 | 1132 | 2.0878 | 33.1015 | 12.5523 | 16.968 | 31.4325 | 1.0 |
| 2.3229 | 2.0 | 2264 | 2.0782 | 39.2573 | 16.2234 | 18.5676 | 38.1963 | 1.0 |
| 2.2209 | 2.9978 | 3393 | 2.0896 | 46.0449 | 15.3846 | 20.0708 | 44.1558 | 1.0 |

#### Framework versions

[Read the full model card (162 words)](https://savrn.com/models/led-large-16384-base3ep-asprpreace3ep/card)

## Configuration

Architecture

MultiTask_LED

Layers

12

Vocabulary size

50,265

Stored precision

float32

Model type

led

## Identity and Version

Repository

rosadecsai/led-large-16384-BASE3ep-ASPRPreACE3ep

Publisher

Rosa Rodriguez-Sánchez

Task

Not stated by the source

Modality

Other

Library

transformers

Parameters

460M parameters

Languages

led

Revision

90f199862c6cc7f2233456c0b169014e7989f46a

First published

2026-09-23

Last updated

2026-09-29

## Files and Weights

14 files, 1.8 GB in total. The weights are 2 files totalling 1.8 GB in bin, safetensors.

Weights2 files · 1.8 GB

Configuration3 files · 2.7 KB

Tokenizer4 files · 4.8 MB

Documentation1 file · 2.1 KB

Other3 files · 32.6 KB

Repository1 file · 1.5 KB

Every file

| File | Type | Size | SHA-256 |
| --- | --- | --- | --- |
| model.safetensors | Weights | 1.8 GB | 17161ab1c946 |
| training_args.bin | Weights | 8.1 KB | 868cb6cb5d2e |
| config.json | Configuration | 1.4 KB | — |
| generation_config.json | Configuration | 303 B | — |
| special_tokens_map.json | Configuration | 957 B | — |
| README.md | Documentation | 2.1 KB | — |
| runs/Sep23_17-00-06_ea84f59ae7ce/events.out.tfevents.1790182814.ea84f59ae7ce.1911.0 | Other | 11.2 KB | 4d05261122c3 |
| runs/Sep24_08-57-51_d6031ce138c3/events.out.tfevents.1790240288.d6031ce138c3.668.0 | Other | 11.2 KB | e31d7f37bffc |
| runs/Sep28_16-09-40_1e1d46e6fde9/events.out.tfevents.1790611796.1e1d46e6fde9.1591.0 | Other | 10.1 KB | 64cf4a9ff6f4 |
| .gitattributes | Repository | 1.5 KB | — |
| merges.txt | Tokenizer | 456.3 KB | — |
| tokenizer.json | Tokenizer | 3.6 MB | — |
| tokenizer_config.json | Tokenizer | 1.2 KB | — |
| vocab.json | Tokenizer | 798.3 KB | — |

## License and Download

License

apache-2.0

Access

Open weights, no gate

Download size

1.8 GB

[Download from Rosa Rodriguez-Sánchez](https://huggingface.co/rosadecsai/led-large-16384-BASE3ep-ASPRPreACE3ep)

Released by Rosa Rodriguez-Sánchez through its official repository on Hugging Face. [Read the license](https://www.apache.org/licenses/LICENSE-2.0).

## Built From

- Derived from rosadecsai/led-large-16384-BASE3ep

## Memory Requirements

| Precision | Weights in memory |
| --- | --- |
| As published | 1.8 GB |
| 16-bit | 0.9 GB |
| 8-bit | 0.5 GB |
| 4-bit | 0.2 GB |

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

## Questions About led-large-16384-BASE3ep-ASPRPreACE3ep

### How much GPU memory does led-large-16384-BASE3ep-ASPRPreACE3ep need?

About 1.1 GB at 16-bit and 0.3 GB at 4-bit: the weights (460M parameters) plus a working margin. A long context needs more.

### What is the cheapest GPU to run led-large-16384-BASE3ep-ASPRPreACE3ep 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.

### Can I use led-large-16384-BASE3ep-ASPRPreACE3ep commercially?

Yes. led-large-16384-BASE3ep-ASPRPreACE3ep is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

## Rosa Rodriguez-Sánchez

[All models and datasets](https://savrn.com/model-publishers/rosadecsai)

## Versions

- [90f199862c6c](https://savrn.com/models/led-large-16384-base3ep-asprpreace3ep/versions/90f199862c6c) · current 2026-09-29

## Explore More

- [All models under apache-2.0](https://savrn.com/models/licenses/apache-2-0)
- [Model comparisons](https://savrn.com/models/comparisons)
- [The model directory](https://savrn.com/models)
- [Open model prices by host](https://savrn.com/ai-index/pricing/open-models)

## Source

- Repository metadata, read 2026-09-29.
- [Hugging Face record](https://huggingface.co/rosadecsai/led-large-16384-BASE3ep-ASPRPreACE3ep)
- [How the hub is built](https://savrn.com/model-hub/methodology)