metadata
license: other
license_name: nvidia-open-model-license
license_link: >-
https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf
inference: false
fine-tuning: false
tags:
- fp8
- vllm
base_model: mgoin/Nemotron-4-340B-Base-hf
Nemotron-4-340B-Base-hf-FP8
Converted and quantized checkpoint of nvidia/Nemotron-4-340B-Base. Specifically it was produced from the v1.2 .nemo checkpoint on NGC.
You can deploy this model with vllm>=0.5.4 (PR#6611):
vllm serve mgoin/Nemotron-4-340B-Base-hf-FP8 --tensor-parallel-size 8
Evaluations
All the below evaluations were run with lm-eval==0.4.3 on 8xA100 GPUs.
lm_eval --model vllm --model_args pretrained=/home/mgoin/code/Nemotron-4-340B-Base-hf-FP8,tensor_parallel_size=8,distributed_executor_backend="ray",max_model_len=4096,gpu_memory_utilization=0.6 --tasks truthfulqa_mc2 --num_fewshot 0 --batch_size 16
vllm (pretrained=/home/mgoin/code/Nemotron-4-340B-Base-hf-FP8,tensor_parallel_size=8,distributed_executor_backend=ray,max_model_len=4096,gpu_memory_utilization=0.6), gen_kwargs: (None), limit: None, num_fewshot: 0, batch_size: 16
| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr|
|--------------|------:|------|-----:|------|---|-----:|---|-----:|
|truthfulqa_mc2| 2|none | 0|acc |↑ |0.4869|± |0.0142|
lm_eval --model vllm --model_args pretrained=/home/mgoin/code/Nemotron-4-340B-Base-hf-FP8,tensor_parallel_size=8,distributed_executor_backend="ray",max_model_len=4096,gpu_memory_utilization=0.6 --tasks winogrande --num_fewshot 5 --batch_size 16
vllm (pretrained=/home/mgoin/code/Nemotron-4-340B-Base-hf-FP8,tensor_parallel_size=8,distributed_executor_backend=ray,max_model_len=4096,gpu_memory_utilization=0.6), gen_kwargs: (None), limit: None, num_fewshot: 5, batch_size: 16
| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr|
|----------|------:|------|-----:|------|---|-----:|---|-----:|
|winogrande| 1|none | 5|acc |↑ |0.8887|± |0.0088|
The original paper evals for reference:
The Minitron paper has more evals as well:
