InternLM

InternLM 7B

Name: InternLM 7B
Rating: 69 (142 reviews)
Author: InternLM

旧版

HuggingFace

1.8K下载量96点赞Jul 2023发布日期8K tokens上下文Apache 2.0许可证50 良好质量

InternLM 7B (7B parameters) requires approximately 13.9 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 16 GB of VRAM.

快速开始

— 复制粘贴即可本地运行

Copy-paste commands to run InternLM 7B on your machine.

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
  --hf-repo "InternLM/InternLM-7B" \
  --hf-file "InternLM-7B-Q4_K_M.gguf" \
  -c 4096 -ngl 99

Quick specs

Parameters7B

Architecturedense

Context8K tokens

Modalitytext

Min RAM2.7 GB

Rec. RAM4.3 GB (Q4_K_M)

LicenseApache 2.0

FamilyInternLM

✓ Chat✓ Reasoning

About this model

InternLM has open-sourced a 7 billion parameter base model tailored for practical scenarios. The model has the following characteristics: - It leverages trillions of high-quality tokens for training to establish a powerful knowledge base. - It provides a versatile toolset for users to flexibly build their own workflows.

•It leverages trillions of high-quality tokens for training to establish a powerful knowledge base
•It provides a versatile toolset for users to flexibly build their own workflows

InternLM 7B 的最佳选择

运行此模型

InternLM 7B on RX 7900 XT 20GB InternLM 7B on RTX A4500 20GB InternLM 7B on RTX 3090 24GB

量化选项

各量化级别的 VRAM 估算

No hardware detected — fit column shows raw VRAM estimates

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	—
Q3_K_S	3	3.4 GB	Low	—
NVFP4	4	3.9 GB	Medium	—
Q4_K_M	4	4.3 GB	Medium	—
Q5_K_M	5	5.0 GB	High	—
Q6_K	6	5.7 GB	High	—
Q8_0	8	7.5 GB	Very High	—
F16	16	14.3 GB	Maximum	—

硬件兼容性

全部硬件的适配估算

打开计算器

Computing compatibility...

内存详细分析

Reference: RTX 2060 6GB

Weights4.3 GB

KV Cache7.8 GB

Runtime1.2 GB

Headroom0.6 GB

常见问题

FAQ — InternLM 7B

另请参阅

量化指南评分方法打开计算器