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Open-weight model · Text generation

TCM-Qwen2.5-7B-SFT-V1

by Xiao Xxiao2023/TCM-Qwen2.5-7B-SFT-V1

TCM-Qwen2.5-7B-SFT-V1 is an open-weight model for text generation from Xiao, released under Apache License 2.0. It has 7.6B parameters and a 131,072-token context. At 16-bit it needs about 18.3 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index. It draws 10 downloads a month.

基于 Qwen2.5-7B 的中医领域继续预训练与监督微调模型。 - 基座模型：Qwen/Qwen2.5-7B - 架构：Qwen2 - 训练方式：中医 CPT + SFT - 权重格式：Safetensors 本模型以 Qwen/Qwen2.5-7B 为基座。使用和分发时请同时遵守基座模型及相关训练数据的适用许可与条款。

Parameters7.6B
Context131,072
Weights15.2 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads10

Runs On

What it takes to serve TCM-Qwen2.5-7B-SFT-V1 (7.6B 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 15.2 GB 18.3 GB 1x MI300X (192 GB)
Vultr		 $1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 7.6 GB 9.1 GB 1x MI300X (192 GB)
Vultr		 $1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 3.8 GB 4.6 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 18, 2026.

TCM-Qwen2.5-7B-SFT-V1 on every accelerator the SAVRN Index prices, at every precision

Model Card

By Xiao, published under apache-2.0, revision 471ddc31f354.

基于 Qwen2.5-7B 的中医领域继续预训练与监督微调模型。 - 基座模型：Qwen/Qwen2.5-7B - 架构：Qwen2 - 训练方式：中医 CPT + SFT - 权重格式：Safetensors 本模型以 Qwen/Qwen2.5-7B 为基座。使用和分发时请同时遵守基座模型及相关训练数据的适用许可与条款。

Read Xiao's full model card

TCM-Qwen2.5-7B-SFT-V2

基于 Qwen2.5-7B 的中医领域继续预训练与监督微调模型。

模型信息

  • 基座模型：Qwen/Qwen2.5-7B
  • 架构：Qwen2
  • 训练方式：中医 CPT + SFT
  • 版本：V2
  • 权重格式：Safetensors
  • 主要语言：中文
  • 适用方向：中医知识问答、文本理解与安全边界辅助。

使用限制

本模型仅供研究、教育和辅助性文本生成使用，不能替代执业医师的诊断、处方或治疗决策。医疗相关输出应由具备资质的专业人员审核；紧急情况请及时就医。

许可与致谢

本模型以 Qwen/Qwen2.5-7B 为基座。使用和分发时请同时遵守基座模型及相关训练数据的适用许可与条款。

Configuration

Architecture
Qwen2ForCausalLM
Context length (tokens)
131,072
Layers
28
Hidden size
3,584
Feed-forward size
18,944
Attention heads
28
Key/value heads
4
Vocabulary size
152,064
Model type
qwen2

Identity and Version

Repository
Xxiao2023/TCM-Qwen2.5-7B-SFT-V1
Publisher
Xiao
Task
Text generation
Modality
Text
Library
transformers
Parameters
7.6B parameters
Languages
zh
Revision
471ddc31f3542e9d7409f7a3434404374aad005f
First published
2026-10-07
Last updated
2026-10-08

Files and Weights

12 files, 15.2 GB in total. The weights are 4 files totalling 15.2 GB in safetensors.

Weights4 files · 15.2 GB
Configuration3 files · 29.4 KB
Tokenizer2 files · 11.4 MB
Documentation1 file · 922 B
Other1 file · 2.4 KB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
model-00001-of-00004.safetensorsWeights4.0 GB 95b9c1e75cdc
model-00002-of-00004.safetensorsWeights3.9 GB 722164ddc671
model-00003-of-00004.safetensorsWeights3.9 GB 88eb47dfb870
model-00004-of-00004.safetensorsWeights3.5 GB e5eceaf20353
config.jsonConfiguration1.4 KB —
generation_config.jsonConfiguration165 B —
model.safetensors.index.jsonConfiguration27.8 KB —
README.mdDocumentation922 B —
chat_template.jinjaOther2.4 KB —
.gitattributesRepository1.6 KB —
tokenizer.jsonTokenizer11.4 MB 3fd169731d2c
tokenizer_config.jsonTokenizer693 B —

License and Download

License
apache-2.0
Access
Open weights, no gate
Download size
15.2 GB
Download from Xiao

Released by Xiao through its official repository on Hugging Face. Read the license.

Built From

Memory Requirements

PrecisionWeights in memory
As published15.2 GB
16-bit15.2 GB
8-bit7.6 GB
4-bit3.8 GB

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

Questions About TCM-Qwen2.5-7B-SFT-V1

How much GPU memory does TCM-Qwen2.5-7B-SFT-V1 need?

About 18.3 GB at 16-bit and 4.6 GB at 4-bit: the weights (7.6B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run TCM-Qwen2.5-7B-SFT-V1 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 TCM-Qwen2.5-7B-SFT-V1 commercially?

Yes. TCM-Qwen2.5-7B-SFT-V1 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.

What is TCM-Qwen2.5-7B-SFT-V1's context length?

131,072 tokens, from the maximum position embeddings in its published configuration.

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