# uuu_fine_tune_gpt2 by David Lanz: Open-Weight Model Source: https://savrn.com/models/uuu-fine-tune-gpt2 Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- ## Runs On What it takes to serve uuu_fine_tune_gpt2 (102M 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 | 0.2 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 | 0.1 GB | 0.1 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 | | 4-bit | 0.1 GB | 0.1 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 | 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 7, 2026. [uuu_fine_tune_gpt2 on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/uuu-fine-tune-gpt2/gpus) ## Model Card Fine tuning pre-trained language models for text generation. Pretrained model on Chinese language using a GPT2 for Large Language Head Model objective. transferlearning from DavidLanz/uuufinetunetaipower and fine-tuning with medical dataset for the GPT-2 architecture. You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we Excerpt from the card by David Lanz, licensed gpl. ## Configuration Architecture GPT2LMHeadModel Vocabulary size 21,128 Model type gpt2 ## Identity and Version Repository DavidLanz/uuu_fine_tune_gpt2 Publisher David Lanz Task Text generation Modality Text Library transformers Parameters 102M parameters Languages en Revision 9b278f8da90656ec2e8252813ceac34d4b03ecde First published 2023-10-17 Last updated 2026-10-04 ## Files and Weights 12 files, 817.2 MB in total. The weights are 3 files totalling 816.6 MB in bin, safetensors. Weights3 files · 816.6 MB Configuration4 files · 1.9 KB Tokenizer3 files · 549.3 KB Documentation1 file · 1.7 KB Repository1 file · 1.5 KB Every file | File | Type | Size | SHA-256 | | --- | --- | --- | --- | | model.safetensors | Weights | 408.3 MB | 2258bb4f56c6 | | pytorch_model.bin | Weights | 408.3 MB | 898d3cf80083 | | training_args.bin | Weights | 5.2 KB | 2b9585d1ce36 | | added_tokens.json | Configuration | 82 B | — | | config.json | Configuration | 1.0 KB | — | | generation_config.json | Configuration | 115 B | — | | special_tokens_map.json | Configuration | 695 B | — | | README.md | Documentation | 1.7 KB | — | | .gitattributes | Repository | 1.5 KB | — | | tokenizer.json | Tokenizer | 439.2 KB | — | | tokenizer_config.json | Tokenizer | 540 B | — | | vocab.txt | Tokenizer | 109.5 KB | — | ## License and Download License gpl Access Open weights, no gate Download size 816.6 MB [Download from David Lanz](https://huggingface.co/DavidLanz/uuu_fine_tune_gpt2) Released by David Lanz through its official repository on Hugging Face. ## Memory Requirements | Precision | Weights in memory | | --- | --- | | As published | 816.6 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 uuu_fine_tune_gpt2 ### How much GPU memory does uuu_fine_tune_gpt2 need? About 0.2 GB at 16-bit and 0.1 GB at 4-bit: the weights (102M parameters) plus a working margin. A long context needs more. ### What is the cheapest GPU to run uuu_fine_tune_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. ### What license is uuu_fine_tune_gpt2 released under? gpl, as its publisher declares it. Read the license text before commercial use. ## Similar Models Model · Text generation ### [Myosotis-1-base](https://savrn.com/models/myosotis-1-base) [FWKV Project](https://savrn.com/model-publishers/fwkv) Myosotis-1-base is the first flagship release from us, introducing a 100-million parameter recurrent language model built on the FWKV architecture. Myosotis-1 is engineered to never truly forget—using a mathematically clamped exponential decay that guarantees an infinite effective context window while maintaining blazing-fast inference on consumer hardware. Instead of pairwise attention, Myosotis uses a fixed-size state vector updated via a gated linear recurrence: $$ St = S{t-1} \odot W + kt \odot vt $$ - \\( W = \text{clamp}(\sigma(w), 0.1) \\) is a learned, constant-per-channel decay. - By clamping the minimum decay to 0.1, the model guarantees that past information decays exponentially… Open weights apache-2.0 102M parameters transformers [View model](https://savrn.com/models/myosotis-1-base) Model · Text generation ### [macbert4csc-base-chinese](https://savrn.com/models/macbert4csc-base-chinese) [Ming Xu (徐明)](https://savrn.com/model-publishers/shibing624) macbert4csc-base-chinese evaluate SIGHAN2015 test data： 由于训练使用的数据使用了SIGHAN2015的训练集（复现paper），在SIGHAN2015的测试集上达到SOTA水平。 模型结构，魔改于softmaskedbert： 本项目开源在中文文本纠错项目：pycorrector，可支持macbert4csc模型，通过如下命令调用： 当然，你也可使用transformers调用： SIGHAN+Wang271K中文纠错数据集，数据格式： 如果需要训练macbert4csc，请参考https://github.com/shibing624/pycorrector/tree/master/pycorrector/macbert MacBERT is an improved BERT with novel MLM as correction pre-training task, which mitigates the discrepancy of pre-training and fine-tuning. 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It is a complete, small, from-scratch GPT, with its training… Open weights apache-2.0 98M parameters pytorch [View model](https://savrn.com/models/lmlm-97m-1) ## David Lanz [All models and datasets](https://savrn.com/model-publishers/davidlanz) ## Versions - [9b278f8da906](https://savrn.com/models/uuu-fine-tune-gpt2/versions/9b278f8da906) · current 2026-10-04 ## Explore More - [All text generation models](https://savrn.com/models/tasks/text-generation) - [All models under gpl](https://savrn.com/models/licenses/gpl) - [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 2026-10-04. - [Hugging Face record](https://huggingface.co/DavidLanz/uuu_fine_tune_gpt2) - [How the hub is built](https://savrn.com/model-hub/methodology)