Instructions to use prereasoner/prereasoner-weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use prereasoner/prereasoner-weights with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Readers v14: v14b in slot b, so all four reading models are trained with SynSQL-2.5M's databases; the choice over both re-scorers refitted on their pool, threshold 0.0862
Browse files- readers/choice.json +11 -11
- readers/stage2_b/model.pt +1 -1
readers/choice.json
CHANGED
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@@ -1,18 +1,18 @@
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{
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"calibration": {
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-
"choice_cross_validated":
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-
"pool":
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"questions": 1035,
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"readers": 4,
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-
"rescorer_alone":
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},
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"coef": [
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0.
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-
0.
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-
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-
-0.
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-
0.
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-
0.
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],
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"features": [
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"rescorer_a_logit",
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@@ -22,7 +22,7 @@
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"readers_share",
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"empty"
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],
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-
"intercept": -0.
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"matched": {
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"answered": 1021,
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"baseline_wrong": 294,
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@@ -30,5 +30,5 @@
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"right": 727,
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"wrong": 294
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},
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-
"threshold": 0.
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}
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|
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{
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"calibration": {
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+
"choice_cross_validated": 734,
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+
"pool": 865,
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"questions": 1035,
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"readers": 4,
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+
"rescorer_alone": 685
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},
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"coef": [
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+
0.2152887149555456,
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+
0.21051980600773687,
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+
0.3248892014544305,
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+
-0.07945837102120888,
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+
0.7014739734689849,
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+
-0.0754918469748226
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],
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"features": [
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"rescorer_a_logit",
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|
|
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"readers_share",
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"empty"
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| 24 |
],
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+
"intercept": -0.7039032072758181,
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| 26 |
"matched": {
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| 27 |
"answered": 1021,
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| 28 |
"baseline_wrong": 294,
|
|
|
|
| 30 |
"right": 727,
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| 31 |
"wrong": 294
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},
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+
"threshold": 0.0862
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}
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readers/stage2_b/model.pt
CHANGED
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 1124924775
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:f67fe7ee4c0d2eabe1472e4c7a55b597222f5132a29d6778d041b92fe7cf2203
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size 1124924775
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