Text Classification
Transformers
Safetensors
English
emcoder
emotion-recognition
bayesian-deep-learning
mc-dropout
uncertainty-quantification
multi-label-classification
custom_code
Eval Results (legacy)
Instructions to use yezdata/EmCoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yezdata/EmCoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yezdata/EmCoder", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("yezdata/EmCoder", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Delete thresholds.json
Browse files- thresholds.json +0 -114
thresholds.json
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{
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"admiration": {
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"p": 0.6714285714285715,
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"f1": 0.6646403242147924
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},
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"amusement": {
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"p": 0.6714285714285715,
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"f1": 0.7877862595419848
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},
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"anger": {
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"p": 0.5571428571428572,
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"f1": 0.43231441048034935
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},
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"annoyance": {
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"p": 0.3857142857142858,
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"f1": 0.32748538011695905
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},
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"approval": {
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"p": 0.3285714285714286,
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"f1": 0.30103480714957664
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},
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"caring": {
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"p": 0.6714285714285715,
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"f1": 0.33440514469453375
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},
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"confusion": {
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"p": 0.6714285714285715,
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"f1": 0.3940520446096654
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},
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"curiosity": {
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"p": 0.5571428571428572,
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"f1": 0.5225225225225225
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},
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"desire": {
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"p": 0.7285714285714286,
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"f1": 0.5228758169934641
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},
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"disappointment": {
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"p": 0.5571428571428572,
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"f1": 0.2638888888888889
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},
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"disapproval": {
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"p": 0.3857142857142858,
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},
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"embarrassment": {
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"p": 0.8428571428571429,
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"f1": 0.5454545454545454
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},
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"excitement": {
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"p": 0.6714285714285715,
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"f1": 0.29411764705882354
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},
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"fear": {
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"p": 0.7857142857142857,
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"f1": 0.5365853658536586
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"gratitude": {
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"p": 0.8428571428571429,
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"f1": 0.9135446685878963
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"grief": {
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"p": 0.5571428571428572,
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"f1": 0.4166666666666667
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"joy": {
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"p": 0.7857142857142857,
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"f1": 0.5679012345679012
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},
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"love": {
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"p": 0.7857142857142857,
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"f1": 0.7805755395683454
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"nervousness": {
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"p": 0.6714285714285715,
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"f1": 0.4
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},
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"optimism": {
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"p": 0.6714285714285715,
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"f1": 0.5983827493261455
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},
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"pride": {
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"p": 0.6714285714285715,
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"f1": 0.6666666666666666
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},
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"realization": {
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"p": 0.5571428571428572,
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"f1": 0.24390243902439024
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"relief": {
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"p": 0.7285714285714286,
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"f1": 0.24
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"remorse": {
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"p": 0.7857142857142857,
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"f1": 0.7682119205298014
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"sadness": {
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"p": 0.6142857142857143,
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"f1": 0.4875
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"surprise": {
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"p": 0.6714285714285715,
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"neutral": {
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"f1": 0.6542099192618224
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