|
--- |
|
license: apache-2.0 |
|
--- |
|
|
|
### DISTILBERT RUNNING ON [DEEPSPARSE](https://github.com/neuralmagic/deepsparse) GOES BRHMMMMMMMM. πππ |
|
|
|
This model is π |
|
|
|
ββββββββ βββββββ ββββββ βββββββ ββββββββ ββββββββ |
|
ββββββββ ββββββββ ββββββββ ββββββββ ββββββββ ββββββββ |
|
ββββββββ ββββββββ ββββββββ ββββββββ ββββββββ ββββββ |
|
ββββββββ βββββββ ββββββββ ββββββββ βββββββββ βββββ |
|
ββββββββ βββ βββ βββ βββ ββ βββββββββ ββββββββ |
|
ββββββββ βββ βββ βββ βββ ββ βββββββββ ββββββββ |
|
|
|
 |
|
|
|
|
|
### LOOKS LIKE THIS π |
|
|
|
 |
|
|
|
### Inference endpoints, outside of outliers (4ms) is avg. latency on 2 vCPUs: |
|
|
|
 |
|
|
|
|
|
### Handler for access to inference endpoints |
|
|
|
```python |
|
class EndpointHandler: |
|
|
|
def __init__(self, path=""): |
|
|
|
self.pipeline = Pipeline.create(task="text-classification", model_path=path) |
|
|
|
def __call__(self, data: Dict[str, Any]) -> Dict[str, str]: |
|
""" |
|
Args: |
|
data (:obj:): prediction input text |
|
""" |
|
inputs = data.pop("inputs", data) |
|
|
|
start = perf_counter() |
|
prediction = self.pipeline(inputs) |
|
end = perf_counter() |
|
latency = end - start |
|
|
|
return { |
|
"labels": prediction.labels, |
|
"scores": prediction.scores, |
|
"latency (secs.)": latency |
|
} |
|
``` |
|
|
|
Μ·ΜΝ |
|
Μ΅ΝΜ³RΜΆΝΜiΜΈΝΜcΜ΄ΜΜ»kΜΈΜΝyΜ·ΝΜ³ |
|
ΜΈΜΜͺ |
|
Μ·ΝΝ |