The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper
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2402.17764
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Published
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607
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142
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shing3232
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这个模型得什么配置能运行起来啊
3
#13 opened 2 months ago
by
demo001s
CUDA运行不了BF16模型？
2
#1 opened 8 months ago
by
NeuronAstate
Please post f16 quantization.
8
#1 opened 8 months ago
by
ZeroWw
What are the diffences of this with Qwen/CodeQwen1.5-7B
6
#5 opened 9 months ago
by
Kalemnor
请问这个版本GPU内存消耗28G与14B对比如何?
7
#7 opened 10 months ago
by
william0014
How is the inference so fast in this free hardware space?
2
#1 opened 10 months ago
by
mahiatlinux
Would there a chance Jamba to be train in 1.58bit weight?
1
#22 opened 10 months ago
by
shing3232
commented
a
paper
10 months ago
这个矩阵用于常规中文模型量化效果会好吗？
1
#2 opened 10 months ago
by
DesperateZero
commented
3
papers
10 months ago
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper
•
2402.17764
•
Published
•
607
•
142
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper
•
2402.17764
•
Published
•
607
•
142
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper
•
2402.17764
•
Published
•
607
•
142
Upload sakura0.9_1.8B_IQ4NL.gguf
1
#1 opened 11 months ago
by
shing3232
commented
6
papers
11 months ago
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper
•
2402.17764
•
Published
•
607
•
142
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper
•
2402.17764
•
Published
•
607
•
142
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper
•
2402.17764
•
Published
•
607
•
142
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper
•
2402.17764
•
Published
•
607
•
142
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper
•
2402.17764
•
Published
•
607
•
142
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper
•
2402.17764
•
Published
•
607
•
142
add GPTQ, AWQ, and GGUFF formats
4
#11 opened 12 months ago
by
nonetrix