kossisoroyce

3 ms·

1. 1.▲
   Show HN: 10k harmonized time-series datasets of African data(huggingface.co)

   2 points by kossisoroyce 4mo ago|0 comments
2. 2.▲
   by kossisoroyce 7mo ago

   TBVH I didn't think about naming it too much. I defaulted to Ollama because of the perceive simplicity and I wanted that same perceived simplicity to help adoption.
3. 3.▲
   by kossisoroyce 7mo ago

   I'll check this out as soon as I am at my desk.
4. 4.▲
   by kossisoroyce 7mo ago

   Exactly. The objective is to abstract away completely. Shared libraries just add too much overhead.
5. 5.▲
   by kossisoroyce 7mo ago

   I owe you a beer!
6. 6.▲
   by kossisoroyce 7mo ago

   You're welcome!
7. 7.▲
   by kossisoroyce 7mo ago

   The motivation was edge and latency-critical use cases on a product I consulted on. Feature vectors arrived pre-formed and a Python runtime in the hot path wass a non-starter. You're right that for most pipelines the transformation ste
8. 8.▲
   by kossisoroyce 7mo ago

   Fair point in general, but the risk profile here is actually quite low. The generated C is purely computational, with no heap allocation, no pointer arithmetic, no user-controlled memory, no IO. It's essentially a deeply nested if&#x2F
9. 9.▲
   by kossisoroyce 7mo ago

   Glad you got it just in time!
10. 10.▲
    Show HN: Timber – Ollama for classical ML models, 336x faster than Python(github.com)

    207 points by kossisoroyce 7mo ago|33 comments