What are the hardware requirements for Taiwan LLM 7B V2.0 Chat?

Taiwan LLM 7B V2.0 Chat requires approximately 13.5 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Taiwan LLM 7B V2.0 Chat and how large is it?

Taiwan LLM 7B V2.0 Chat is developed by yentinglin, a model with 7b parameters. 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 Taiwan LLM 7B V2.0 Chat?

Taiwan LLM 7B V2.0 Chat is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Taiwan LLM 7B V2.0 Chat by yentinglin — VRAM 13.5GB, 4K context

Name: Taiwan LLM 7B V2.0 Chat
Author: yentinglin

Taiwan LLM 7B V2.0 Chat is an open-source language model by yentinglin. Features: 7b LLM, VRAM: 13.5GB, Context: 4K, License: apache-2.0, LLM Explorer Score: 0.09.

Arxiv:2311.17487 Conversational Endpoints compatible Llama Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/yentinglin/Taiwan-LLM-7B-v2.0-chat

Taiwan LLM 7B V2.0 Chat Parameters and Internals

Model Type

text-generation, GPT-like model

Supported Languages

Traditional Chinese (zh-tw) (Primary)

Training Details

Data Sources:

publicly available datasets, synthetic datasets

Methodology:

Supervised Fine-Tuning

Model Architecture:

GPT-like

LLM Name	Taiwan LLM 7B V2.0 Chat
Repository 🤗	https://huggingface.co/yentinglin/Taiwan-LLM-7B-v2.0-chat
Model Size	7b
Required VRAM	13.5 GB
Updated	2026-08-08
Maintainer	yentinglin
Model Type	llama
Model Files	10.0 GB: 1-of-2 3.5 GB: 2-of-2
Supported Languages	zh
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.34.0
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Taiwan LLM 7B V2.0 Chat 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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Note: green Score (e.g. "73.2") means that the model is better than yentinglin/Taiwan-LLM-7B-v2.0-chat.