What are the hardware requirements for Bert Chinese L 12 H 768 A 12?

Bert Chinese L 12 H 768 A 12 requires approximately 0.4 GB of VRAM and supports a context window of 0.5K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Bert Chinese L 12 H 768 A 12 and how large is it?

Bert Chinese L 12 H 768 A 12 is developed by Tongjilibo. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Bert Chinese L 12 H 768 A 12?

Bert Chinese L 12 H 768 A 12 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Bert Chinese L 12 H 768 A 12 by Tongjilibo — VRAM 0.4GB, 0.5K context

Name: Bert Chinese L 12 H 768 A 12
Author: Tongjilibo

Bert Chinese L 12 H 768 A 12 is an open-source language model by Tongjilibo. Features: LLM, VRAM: 0.4GB, Context: 0.5K, License: apache-2.0, LLM Explorer Score: 0.11.

Endpoints compatible Pytorch Region:us

Model Card on HF 🤗: https://huggingface.co/Tongjilibo/bert-chinese_L-12_H-768_A-12

Bert Chinese L 12 H 768 A 12 Parameters and Internals

Model Type

Text Embedding, Transformer

Use Cases

Areas:

Research, Natural Language Processing

Applications:

Syntactic and semantic text analysis, Text embedding generation

Primary Use Cases:

Chinese text embedding for natural language understanding tasks

Additional Notes

The BERT 'chinese_L-12_H-768_A-12' and 'bert-base-chinese' weights are reportedly the same.

Supported Languages

Chinese (Proficient)

Training Details

Data Sources:

Chinese datasets

Methodology:

Transformer architecture

Context Length:

512

Model Architecture:

12-layer, 768-hidden, 12-heads BERT architecture

Input Output

Input Format:

Tokenized input sequences

Accepted Modalities:

text

Output Format:

Text embeddings

Performance Tips:

Use pre-trained models for enhanced language understanding

LLM Name	Bert Chinese L 12 H 768 A 12
Repository 🤗	https://huggingface.co/Tongjilibo/bert-chinese_L-12_H-768_A-12
Required VRAM	0.4 GB
Updated	2026-06-25
Maintainer	Tongjilibo
Model Files	0.4 GB
Model Architecture	AutoModel
License	apache-2.0
Context Length	512
Model Max Length	512
Vocabulary Size	21128

Rank the Bert Chinese L 12 H 768 A 12 capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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Opengpt2 Pytorch Forward	1K / 6 GB	2	1
Finsent Transformer	0.5K / 0.4 GB	1	1
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All MiniLM L12 V2	0.5K / GB	1677	4

Note: green Score (e.g. "73.2") means that the model is better than Tongjilibo/bert-chinese_L-12_H-768_A-12.