feat: benchmark.

[b4rtaz]

This PR extends the metrics in inference mode.

...
💿 Weights loaded
Tensor parallelism is all you need. Run LLMs on weak devices or make powerful devices even more powerful by distributing
🔷️ Eval  534 ms Sync  100 ms | Sent  6912 kB Recv 12540 kB | (24 tokens)
🔶 Pred   68 ms Sync   25 ms | Sent   288 kB Recv   522 kB |  them
🔶 Pred   58 ms Sync   15 ms | Sent   288 kB Recv   522 kB |  with
🔶 Pred   57 ms Sync   11 ms | Sent   288 kB Recv   522 kB |  TP
🔶 Pred   43 ms Sync   18 ms | Sent   288 kB Recv   522 kB | .
...
🔶 Pred   47 ms Sync   15 ms | Sent   288 kB Recv   522 kB |  used
🔶 Pred   52 ms Sync   32 ms | Sent   288 kB Recv   522 kB |  in
🔶 Pred   42 ms Sync   11 ms | Sent   288 kB Recv   522 kB |  deep
🔶 Pred   44 ms Sync   10 ms | Sent   288 kB Recv   522 kB |  learning

Evaluation
   nBatches: 32
    nTokens: 24
   tokens/s: 37.83 (26.43 ms/tok)
Prediction
    nTokens: 40
   tokens/s: 16.10 (62.10 ms/tok)