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axolotl/examples/llama-3
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salman 58d67bf98d Migrate QAT API; fix axolotl quantize for QAT-ed models; add NVFP4 (#3107)
2025-09-12 10:55:50 +01:00
..
diffusion
text diffusion training plugin (#3067)
2025-09-10 20:27:00 -04:00
3b-fp8-fsdp2.yaml
basic torchao fp8 mixed precision training (#2926)
2025-07-22 16:27:47 -04:00
3b-qat-fsdp2-nvfp4.yaml
Migrate QAT API; fix axolotl quantize for QAT-ed models; add NVFP4 (#3107)
2025-09-12 10:55:50 +01:00
3b-qat-fsdp2.yaml
Migrate QAT API; fix axolotl quantize for QAT-ed models; add NVFP4 (#3107)
2025-09-12 10:55:50 +01:00
fft-8b-liger-fsdp.yaml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
fft-8b.yaml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
instruct-dpo-lora-8b.yml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
instruct-lora-8b.yml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
lora-1b-deduplicate-dpo.yml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
lora-1b-deduplicate-sft.yml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
lora-1b-kernels.yml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
lora-1b-ray.yml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
lora-1b-sample-packing-sequentially.yml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
lora-1b.yml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
lora-8b.yml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
qlora-1b-kto.yaml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
qlora-1b.yml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
qlora-fsdp-70b.yaml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
qlora-fsdp-405b.yaml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
qlora.yml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00
README.md
llama-3 examples (#1537)
2024-04-18 14:28:03 -04:00
sparse-finetuning.yaml
use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
2025-07-30 06:44:06 -04:00

README.md

Llama-3

https://llama.meta.com/llama3/

8B Base Model

70B Base Model

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