nlp-lab5-8-gpt2 is an open-weight model from Rattapoommaru, released under MIT License. It has 124M parameters. At 16-bit it needs about 0.3 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.
โมเดล GPT-2 ภาษาไทยที่ปรับแต่งด้วยชุดข้อมูลประโยคภาษาไทยของข้อสอบ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Use the code below to get started with the model.
Runs On
What it takes to serve nlp-lab5-8-gpt2 (124M 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 | 0.2 GB | 0.3 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 0.1 GB | 0.1 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.
nlp-lab5-8-gpt2 on every accelerator the SAVRN Index prices, at every precision
Model Card
By Rattapoommaru, published under mit, revision 63cd3a8f98a6.
โมเดล GPT-2 ภาษาไทยที่ปรับแต่งด้วยชุดข้อมูลประโยคภาษาไทยของข้อสอบ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Use the code below to get started with the model. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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Model Details
Model Description
โมเดล GPT-2 ภาษาไทยที่ปรับแต่งด้วยชุดข้อมูลประโยคภาษาไทยของข้อสอบ
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- Language(s) (NLP): th
- License: mit
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
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Training Details
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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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Configuration
- Architecture
- GPT2LMHeadModel
- Vocabulary size
- 50,269
- Model type
- gpt2
Identity and Version
- Repository
- RattyC/nlp-lab5-8-gpt2
- Publisher
- Rattapoommaru
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 124M parameters
- Languages
- th
- Revision
- 63cd3a8f98a62effd93d17e5212ba5559d3e1566
- First published
- 2026-10-09
- Last updated
- 2026-10-09
Files and Weights
7 files, 502.3 MB in total. The weights are 1 file totalling 497.8 MB in safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.safetensors | Weights | 497.8 MB | 319dbe19cc9e |
| config.json | Configuration | 997 B | — |
| generation_config.json | Configuration | 140 B | — |
| README.md | Documentation | 5.3 KB | — |
| .gitattributes | Repository | 1.5 KB | — |
| tokenizer.json | Tokenizer | 4.5 MB | — |
| tokenizer_config.json | Tokenizer | 343 B | — |
License and Download
- License
- mit
- Access
- Open weights, no gate
- Download size
- 497.8 MB
Released by Rattapoommaru through its official repository on Hugging Face. Read the license.
Built From
- Described by arXiv:1910.09700
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 497.8 MB |
| 16-bit | 0.2 GB |
| 8-bit | 0.1 GB |
| 4-bit | 0.1 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About nlp-lab5-8-gpt2
How much GPU memory does nlp-lab5-8-gpt2 need?
About 0.3 GB at 16-bit and 0.1 GB at 4-bit: the weights (124M parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run nlp-lab5-8-gpt2 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 nlp-lab5-8-gpt2 commercially?
Yes. nlp-lab5-8-gpt2 is released under MIT License. The MIT License is a short permissive license. It permits commercial use, modification and redistribution, provided the copyright notice and permission notice are included.