Snehal Patel
Snehal Patel
# System information - **OS Platform and Distribution (e.g., Linux Ubuntu 16.04)**: Ubuntu 18 - **TensorFlow Serving installed from (source or binary)**: binary - **TensorFlow Serving version**: 2.2.0 ## **Related...
I've trained a tokenizer with 50k vocab and over 500M sentences. I'm in a situation where I'm encoding many keywords that contains OOV tokens which the tokenizer is doing not-so-good...
I have created a dataset of adding a new entity type, let's say it's "XYZ" entity type and I have combined the new train, valid, test data with original CoNLL...
``` sentence = """This is my second build of the T Series Dell Precision.""" %time nn.predict(text=sentence) ``` with this I can get results as follow: ``` Formatting deploy set from...
Top 4 similar emoji with π by using pre-trained `emoji2vec.txt`: πΏ 0.836434900761 π’ 0.689464867115 πΉ 0.677145779133 π 0.671003580093 I get it, that crying face emoji is kind of more similar...
## Bug Report ### Describe the problem How should I restart / reload my model that has been running inside a tf-serving docker container when it goes out of memory...
I am looking at the cpu utilization and it looks like when I am encoding documents, code is just using 4 cpu even though I have 16. I can't find...