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--- |
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license: mit |
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language: |
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- en |
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tags: |
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- mteb |
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- sparse sparsity quantized onnx embeddings int8 |
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model-index: |
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- name: bge-base-en-v1.5-sparse |
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results: |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_counterfactual |
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name: MTEB AmazonCounterfactualClassification (en) |
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config: en |
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split: test |
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
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metrics: |
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- type: accuracy |
|
value: 75.38805970149254 |
|
- type: ap |
|
value: 38.80643435437097 |
|
- type: f1 |
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value: 69.52906891019036 |
|
- task: |
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type: Classification |
|
dataset: |
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type: mteb/amazon_polarity |
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name: MTEB AmazonPolarityClassification |
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config: default |
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split: test |
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revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
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metrics: |
|
- type: accuracy |
|
value: 90.72759999999998 |
|
- type: ap |
|
value: 87.07910150764239 |
|
- type: f1 |
|
value: 90.71025910882096 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
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name: MTEB AmazonReviewsClassification (en) |
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config: en |
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split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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metrics: |
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- type: accuracy |
|
value: 45.494 |
|
- type: f1 |
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value: 44.917953161904805 |
|
- task: |
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type: Clustering |
|
dataset: |
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type: mteb/arxiv-clustering-p2p |
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name: MTEB ArxivClusteringP2P |
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config: default |
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split: test |
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
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metrics: |
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- type: v_measure |
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value: 46.50495921726095 |
|
- task: |
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type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-s2s |
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name: MTEB ArxivClusteringS2S |
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config: default |
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split: test |
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
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metrics: |
|
- type: v_measure |
|
value: 40.080055890804836 |
|
- task: |
|
type: Reranking |
|
dataset: |
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type: mteb/askubuntudupquestions-reranking |
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name: MTEB AskUbuntuDupQuestions |
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config: default |
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split: test |
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
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metrics: |
|
- type: map |
|
value: 60.22880715757138 |
|
- type: mrr |
|
value: 73.11227630479708 |
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- task: |
|
type: STS |
|
dataset: |
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type: mteb/biosses-sts |
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name: MTEB BIOSSES |
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config: default |
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split: test |
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
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metrics: |
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- type: cos_sim_pearson |
|
value: 86.9542549153515 |
|
- type: cos_sim_spearman |
|
value: 83.93865958725257 |
|
- type: euclidean_pearson |
|
value: 86.00372707912037 |
|
- type: euclidean_spearman |
|
value: 84.97302050526537 |
|
- type: manhattan_pearson |
|
value: 85.63207676453459 |
|
- type: manhattan_spearman |
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value: 84.82542678079645 |
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- task: |
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type: Classification |
|
dataset: |
|
type: mteb/banking77 |
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name: MTEB Banking77Classification |
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config: default |
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split: test |
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
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metrics: |
|
- type: accuracy |
|
value: 84.29545454545455 |
|
- type: f1 |
|
value: 84.26780483160312 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-p2p |
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name: MTEB BiorxivClusteringP2P |
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config: default |
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split: test |
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
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metrics: |
|
- type: v_measure |
|
value: 36.78678386185847 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-s2s |
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name: MTEB BiorxivClusteringS2S |
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config: default |
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split: test |
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
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metrics: |
|
- type: v_measure |
|
value: 34.42462869304013 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/emotion |
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name: MTEB EmotionClassification |
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config: default |
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split: test |
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revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
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metrics: |
|
- type: accuracy |
|
value: 46.705 |
|
- type: f1 |
|
value: 41.82618717355017 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/imdb |
|
name: MTEB ImdbClassification |
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config: default |
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split: test |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
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metrics: |
|
- type: accuracy |
|
value: 83.14760000000001 |
|
- type: ap |
|
value: 77.40813245635195 |
|
- type: f1 |
|
value: 83.08648833100911 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
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name: MTEB MTOPDomainClassification (en) |
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config: en |
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split: test |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
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metrics: |
|
- type: accuracy |
|
value: 92.0519835841313 |
|
- type: f1 |
|
value: 91.73392170858916 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
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name: MTEB MTOPIntentClassification (en) |
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config: en |
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split: test |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
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metrics: |
|
- type: accuracy |
|
value: 72.48974008207935 |
|
- type: f1 |
|
value: 54.812872972777505 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
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name: MTEB MassiveIntentClassification (en) |
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config: en |
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split: test |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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metrics: |
|
- type: accuracy |
|
value: 73.17753866846 |
|
- type: f1 |
|
value: 71.51091282373878 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
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name: MTEB MassiveScenarioClassification (en) |
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config: en |
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split: test |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
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metrics: |
|
- type: accuracy |
|
value: 77.5353059852051 |
|
- type: f1 |
|
value: 77.42427561340143 |
|
- task: |
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type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-p2p |
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name: MTEB MedrxivClusteringP2P |
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config: default |
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split: test |
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revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 32.00163251745748 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-s2s |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
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revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 30.37879992380756 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/mind_small |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 31.714215488161983 |
|
- type: mrr |
|
value: 32.857362140961904 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering |
|
name: MTEB RedditClustering |
|
config: default |
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split: test |
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revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 50.99679402527969 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering-p2p |
|
name: MTEB RedditClusteringP2P |
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config: default |
|
split: test |
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revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 59.28024721612242 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sickr-sts |
|
name: MTEB SICK-R |
|
config: default |
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split: test |
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revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.54645068673153 |
|
- type: cos_sim_spearman |
|
value: 78.64401947043316 |
|
- type: euclidean_pearson |
|
value: 82.36873285307261 |
|
- type: euclidean_spearman |
|
value: 78.57406974337181 |
|
- type: manhattan_pearson |
|
value: 82.33000263843067 |
|
- type: manhattan_spearman |
|
value: 78.51127629983256 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts12-sts |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.3001843293691 |
|
- type: cos_sim_spearman |
|
value: 74.87989254109124 |
|
- type: euclidean_pearson |
|
value: 80.88523322810525 |
|
- type: euclidean_spearman |
|
value: 75.6469299496058 |
|
- type: manhattan_pearson |
|
value: 80.8921104008781 |
|
- type: manhattan_spearman |
|
value: 75.65942956132456 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts13-sts |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.40319855455617 |
|
- type: cos_sim_spearman |
|
value: 83.63807375781141 |
|
- type: euclidean_pearson |
|
value: 83.28557187260904 |
|
- type: euclidean_spearman |
|
value: 83.65223617817439 |
|
- type: manhattan_pearson |
|
value: 83.30411918680012 |
|
- type: manhattan_spearman |
|
value: 83.69204806663276 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts14-sts |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.08942420708404 |
|
- type: cos_sim_spearman |
|
value: 80.39991846857053 |
|
- type: euclidean_pearson |
|
value: 82.68275416568997 |
|
- type: euclidean_spearman |
|
value: 80.49626214786178 |
|
- type: manhattan_pearson |
|
value: 82.62993414444689 |
|
- type: manhattan_spearman |
|
value: 80.44148684748403 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts15-sts |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.70365000096972 |
|
- type: cos_sim_spearman |
|
value: 88.00515486253518 |
|
- type: euclidean_pearson |
|
value: 87.65142168651604 |
|
- type: euclidean_spearman |
|
value: 88.05834854642737 |
|
- type: manhattan_pearson |
|
value: 87.59548659661925 |
|
- type: manhattan_spearman |
|
value: 88.00573237576926 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts16-sts |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.47886818876728 |
|
- type: cos_sim_spearman |
|
value: 84.30874770680975 |
|
- type: euclidean_pearson |
|
value: 83.74580951498133 |
|
- type: euclidean_spearman |
|
value: 84.60595431454789 |
|
- type: manhattan_pearson |
|
value: 83.74122023121615 |
|
- type: manhattan_spearman |
|
value: 84.60549899361064 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (en-en) |
|
config: en-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.60257252565631 |
|
- type: cos_sim_spearman |
|
value: 88.29577246271319 |
|
- type: euclidean_pearson |
|
value: 88.25434138634807 |
|
- type: euclidean_spearman |
|
value: 88.06678743723845 |
|
- type: manhattan_pearson |
|
value: 88.3651048848073 |
|
- type: manhattan_spearman |
|
value: 88.23688291108866 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (en) |
|
config: en |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 61.666254720687206 |
|
- type: cos_sim_spearman |
|
value: 63.83700525419119 |
|
- type: euclidean_pearson |
|
value: 64.36325040161177 |
|
- type: euclidean_spearman |
|
value: 63.99833771224718 |
|
- type: manhattan_pearson |
|
value: 64.01356576965371 |
|
- type: manhattan_spearman |
|
value: 63.7201674202641 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsbenchmark-sts |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 85.14584232139909 |
|
- type: cos_sim_spearman |
|
value: 85.92570762612142 |
|
- type: euclidean_pearson |
|
value: 86.34291503630607 |
|
- type: euclidean_spearman |
|
value: 86.12670269109282 |
|
- type: manhattan_pearson |
|
value: 86.26109450032494 |
|
- type: manhattan_spearman |
|
value: 86.07665628498633 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/scidocs-reranking |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 84.46430478723548 |
|
- type: mrr |
|
value: 95.63907044299201 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.82178217821782 |
|
- type: cos_sim_ap |
|
value: 95.49612561375889 |
|
- type: cos_sim_f1 |
|
value: 91.02691924227318 |
|
- type: cos_sim_precision |
|
value: 90.75546719681908 |
|
- type: cos_sim_recall |
|
value: 91.3 |
|
- type: dot_accuracy |
|
value: 99.67821782178218 |
|
- type: dot_ap |
|
value: 90.55740832326241 |
|
- type: dot_f1 |
|
value: 83.30765279917823 |
|
- type: dot_precision |
|
value: 85.6388595564942 |
|
- type: dot_recall |
|
value: 81.10000000000001 |
|
- type: euclidean_accuracy |
|
value: 99.82475247524752 |
|
- type: euclidean_ap |
|
value: 95.4739426775874 |
|
- type: euclidean_f1 |
|
value: 91.07413010590017 |
|
- type: euclidean_precision |
|
value: 91.8616480162767 |
|
- type: euclidean_recall |
|
value: 90.3 |
|
- type: manhattan_accuracy |
|
value: 99.82376237623762 |
|
- type: manhattan_ap |
|
value: 95.48506891694475 |
|
- type: manhattan_f1 |
|
value: 91.02822580645163 |
|
- type: manhattan_precision |
|
value: 91.76829268292683 |
|
- type: manhattan_recall |
|
value: 90.3 |
|
- type: max_accuracy |
|
value: 99.82475247524752 |
|
- type: max_ap |
|
value: 95.49612561375889 |
|
- type: max_f1 |
|
value: 91.07413010590017 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 60.92486258951404 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering-p2p |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 32.97511013092965 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/stackoverflowdupquestions-reranking |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 52.31647363355174 |
|
- type: mrr |
|
value: 53.26469792462439 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/toxic_conversations_50k |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 70.917 |
|
- type: ap |
|
value: 13.760770628090576 |
|
- type: f1 |
|
value: 54.23887489664618 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/tweet_sentiment_extraction |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 59.49349179400113 |
|
- type: f1 |
|
value: 59.815392064510775 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/twentynewsgroups-clustering |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 47.29662657485732 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twittersemeval2015-pairclassification |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 85.74834594981225 |
|
- type: cos_sim_ap |
|
value: 72.92449226447182 |
|
- type: cos_sim_f1 |
|
value: 68.14611644433363 |
|
- type: cos_sim_precision |
|
value: 64.59465847317419 |
|
- type: cos_sim_recall |
|
value: 72.1108179419525 |
|
- type: dot_accuracy |
|
value: 82.73827263515527 |
|
- type: dot_ap |
|
value: 63.27505594570806 |
|
- type: dot_f1 |
|
value: 61.717543651265 |
|
- type: dot_precision |
|
value: 56.12443292287751 |
|
- type: dot_recall |
|
value: 68.54881266490766 |
|
- type: euclidean_accuracy |
|
value: 85.90332002145796 |
|
- type: euclidean_ap |
|
value: 73.08299660990401 |
|
- type: euclidean_f1 |
|
value: 67.9050313691721 |
|
- type: euclidean_precision |
|
value: 63.6091265268495 |
|
- type: euclidean_recall |
|
value: 72.82321899736148 |
|
- type: manhattan_accuracy |
|
value: 85.87351731537224 |
|
- type: manhattan_ap |
|
value: 73.02205874497865 |
|
- type: manhattan_f1 |
|
value: 67.87532596547871 |
|
- type: manhattan_precision |
|
value: 64.109781843772 |
|
- type: manhattan_recall |
|
value: 72.1108179419525 |
|
- type: max_accuracy |
|
value: 85.90332002145796 |
|
- type: max_ap |
|
value: 73.08299660990401 |
|
- type: max_f1 |
|
value: 68.14611644433363 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twitterurlcorpus-pairclassification |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.84231769317343 |
|
- type: cos_sim_ap |
|
value: 85.65683184516553 |
|
- type: cos_sim_f1 |
|
value: 77.60567077973222 |
|
- type: cos_sim_precision |
|
value: 75.6563071297989 |
|
- type: cos_sim_recall |
|
value: 79.65814598090545 |
|
- type: dot_accuracy |
|
value: 86.85333954282609 |
|
- type: dot_ap |
|
value: 80.79899186896125 |
|
- type: dot_f1 |
|
value: 74.15220098146928 |
|
- type: dot_precision |
|
value: 70.70819946919961 |
|
- type: dot_recall |
|
value: 77.94887588543271 |
|
- type: euclidean_accuracy |
|
value: 88.77634183257655 |
|
- type: euclidean_ap |
|
value: 85.67411484805298 |
|
- type: euclidean_f1 |
|
value: 77.61566374357423 |
|
- type: euclidean_precision |
|
value: 76.23255123255123 |
|
- type: euclidean_recall |
|
value: 79.04989220819218 |
|
- type: manhattan_accuracy |
|
value: 88.79962743043428 |
|
- type: manhattan_ap |
|
value: 85.6494795781639 |
|
- type: manhattan_f1 |
|
value: 77.54222877224805 |
|
- type: manhattan_precision |
|
value: 76.14100185528757 |
|
- type: manhattan_recall |
|
value: 78.99599630428088 |
|
- type: max_accuracy |
|
value: 88.84231769317343 |
|
- type: max_ap |
|
value: 85.67411484805298 |
|
- type: max_f1 |
|
value: 77.61566374357423 |
|
--- |
|
|
|
# bge-base-en-v1.5-sparse |
|
|
|
## Usage |
|
|
|
This is the sparse ONNX variant of the [bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) embeddings model accelerated with [Sparsify](https://github.com/neuralmagic/sparsify) for quantization/pruning and [DeepSparseSentenceTransformers](https://github.com/neuralmagic/deepsparse/tree/main/src/deepsparse/sentence_transformers) for inference. |
|
|
|
```bash |
|
pip install -U deepsparse-nightly[sentence_transformers] |
|
``` |
|
|
|
```python |
|
from deepsparse.sentence_transformers import DeepSparseSentenceTransformer |
|
model = DeepSparseSentenceTransformer('neuralmagic/bge-base-en-v1.5-sparse', export=False) |
|
|
|
# Our sentences we like to encode |
|
sentences = ['This framework generates embeddings for each input sentence', |
|
'Sentences are passed as a list of string.', |
|
'The quick brown fox jumps over the lazy dog.'] |
|
|
|
# Sentences are encoded by calling model.encode() |
|
embeddings = model.encode(sentences) |
|
|
|
# Print the embeddings |
|
for sentence, embedding in zip(sentences, embeddings): |
|
print("Sentence:", sentence) |
|
print("Embedding:", embedding.shape) |
|
print("") |
|
``` |
|
|
|
For general questions on these models and sparsification methods, reach out to the engineering team on our [community Slack](https://join.slack.com/t/discuss-neuralmagic/shared_invite/zt-q1a1cnvo-YBoICSIw3L1dmQpjBeDurQ). |
