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InternLMInternLM

InternLM 20B

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1.1KDownloads94CurtidasJul 2024Publicado8K tokensContextoInternLMLicença22 InicialQualidade

InternLM 20B (20B parameters) requires approximately 34.2 GB of VRAM with Q5_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 40 GB of VRAM.

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Copy-paste commands to run InternLM 20B on your machine.

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \ --hf-repo "internlm/internlm2_5-20b-chat" \ --hf-file "internlm2_5-20b-chat-Q5_K_M.gguf" \ -c 4096 -ngl 99

Quick specs

Parameters20B
Architecturedense
Context8K tokens
Modalitytext
Min RAM7.8 GB
Rec. RAM14.4 GB (Q5_K_M)
LicenseInternLM
FamilyInternLM
Code Chat

About this model

InternLM2.5 has open-sourced a 20 billion parameter base model and a chat model tailored for practical scenarios. The model has the following characteristics:

  • Outstanding reasoning capability: State-of-the-art performance on Math reasoning, surpassing models like Llama3 and Gemma2-27B
  • Stronger tool use: InternLM2.5 supports gathering information from more than 100 web pages, corresponding implementation has be released in...

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Opções de quantização

Estimativas de VRAM por nível de quantização

No hardware detected — fit column shows raw VRAM estimates

QuantBitsVRAMQualityFit
Q2_K
2
7.8 GB
Low
Q3_K_S
3
9.8 GB
Low
NVFP4
4
11.2 GB
Medium
Q4_K_M
4
12.2 GB
Medium
Q5_K_M
5
14.4 GB
High
Q6_K
6
16.4 GB
High
Q8_0
8
21.4 GB
Very High
F16
16
41.0 GB
Maximum

Quality benchmarks

InternLM 20B benchmark scores

Benchmark verified

Reasoning

MMLU-Pro33.3%
GPQA Diamond9.5%
MATH-50040.8%
ARC Challenge

General

Chatbot Arena
IFEval70.1%

Source: community · 2025-01-01

Compatibilidade de hardware

Estimativas de compatibilidade para todo o hardware

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Computing compatibility...

Detalhamento de memória

Reference: RTX 2060 6GB

Weights14.4 GB
KV Cache18.3 GB
Runtime0.9 GB
Headroom0.6 GB

Perguntas frequentes

FAQ — InternLM 20B

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