adds perf plots need conv plots

Signed-off-by: Jonathan Mitchell <jomitchell@nvidia.com>

Author: jomitchellnv

bionemo-recipes/recipes/llama3_native_te/README.md

@@ -67,8 +67,8 @@ def compute_model_pflops(seq_len, global_batch_size, step_time_s):
 
 ### Low precision performance benchmarks
 
-![Performance Benchmarks Low Precision](../../../docs/docs/assets/images/llama3/llama3_1b_fsdp2_tflops.png)
-In the above plot we can see the performance increases as we lower the precision of our transformer layers.
+![Performance Benchmarks Low Precision](../../../docs/docs/assets/images/llama3/llama3_8gpu_tflops.png)
+In the above plot we can see the performance increases as we lower the precision of our transformer layers across the 1B and 8B variant of LLAMA3.
 
 ### Convergence Benchmarks
 
@@ -94,6 +94,10 @@ are due checkpointing, further work will be done to improve training step time s
 Models were trained on 64 NVIDIA H100 GPUs with a micro batch size of 4 and a context length of 4096 for 60,000 steps.
 Training was performed with BF16 precision.
 
+### Low Precision convergence benchmarks
+
+<!-- ....TODO from WandB once ready. -->
+
 ### Distributed Training
 
 This recipe supports distributed training using DDP, FSDP2, and FSDP2 with Context Parallelism, shown in three separate training entrypoints: