Hugging Face's logo

Intel
/
dynamic-minilmv2-L6-H384-squad1.1-int8-static

Question Answering
Transformers
PyTorch
Safetensors
roberta
Inference Endpoints
Model card Files Community
8

Update README.md

#7
by zmadscientist - opened
base: refs/heads/main
←
from: refs/pr/7
Discussion Files changed
+2
-1
Files changed (1) hide show
  1. README.md +2 -1
README.md CHANGED
@@ -8,7 +8,8 @@ The model card has been written in combination by Intel.
8
 
9
  ### QuaLA-MiniLM training process
10
  Figure showing QuaLA-MiniLM training process. To run the model with the best accuracy-efficiency tradeoff per a specific computational budget, we set the length configuration to the best setting found by an evolutionary search to match our computational constraint.
11
- [ArchitecureQuaLA-MiniLM.jpg](ArchitecureQuaLA-MiniLM.jpg)
 
12
 
13
  ### Model license
14
  Licensed under MIT license.
 
8
 
9
  ### QuaLA-MiniLM training process
10
  Figure showing QuaLA-MiniLM training process. To run the model with the best accuracy-efficiency tradeoff per a specific computational budget, we set the length configuration to the best setting found by an evolutionary search to match our computational constraint.
11
+
12
+ ![QuaLA-MiniLMDiagram.png](https://s3.amazonaws.com/moonup/production/uploads/63dc702662dc193e6d460f1b/0BygutFCv80cktKFWtPAK.png)
13
 
14
  ### Model license
15
  Licensed under MIT license.