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README.md

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+
+--
+pipeline_tag: text-classification
+library_name: turftopic
+tags:
+- turftopic
+- topic-modelling
+---
+
+# kardosdrur/testing_s3
+
+This repository contains a topic model trained with the [Turftopic](https://github.com/x-tabdeveloping/turftopic) Python library.
+
+To load and use the model run the following piece of code:
+
+```python
+from turftopic import load_model
+
+model = load_model(kardosdrur/testing_s3)
+model.print_topics()
+```
+
+## Model Structure
+
+The model is structured as follows:
+
+```
+SemanticSignalSeparation(decomposition=FastICA(n_components=10),
+                         vectorizer=CountVectorizer(min_df=10,
+                                                    stop_words='english'))
+```
+
+## Topics
+The topics discovered by the model are the following:
+
+| Topic ID | Highest Ranking | Lowest Ranking |
+| - | - | - |
+| 0 | goaltenders, nhl, bullpen, sabres, goaltender, puckett, leafs, braves, pitchers, canucks | accelerator, malaysia, automobile, accelerators, mazda, automobiles, automotive, vehicle, silicon, britain |
+| 1 | saturn, suzuki, symptoms, jupiter, bmw, exhaust, volvo, engine, mazda, propulsion | wiretapping, wiretaps, nsa, spying, eavesdropping, wiretap, security, encryption, enforcement, safeguarding |
+| 2 | drawbacks, advantages, productivity, efficiency, innovation, economical, disadvantages, proponents, competitiveness, economically | address, instructions, serial, arrived, codes, configured, 9591, 16550, contacting, recieved |
+| 3 | publishes, archives, publisher, scholars, manuscripts, npr, affiliated, revelations, discusses, archive | motorcycling, motorcycles, speeding, motorcycle, driving, motorcyclist, riding, harleys, braking, vehicles |
+| 4 | motherboard, ram, motherboards, processor, cmos, hardware, chipset, chipsets, amd, mb | yale, sunroof, damphousse, library, npr, billboards, balloon, schools, kerosene, nicholas |
+| 5 | palestinians, palestinian, gazans, gaza, genocide, israelis, atrocities, israeli, hamas, holocaust | motorola, mastercard, technician, smartdrive, telephony, transmissions, phones, electronically, voyager, cruising |
+| 6 | spectrometer, makefile, biochemistry, dblspace, bibliography, booklet, bookstores, circumference, nutritional, statistically | uh, um, em, yeah, oh, er, ah, yer, yo, ye |
+| 7 | theology, theological, scripture, theologians, christianity, biblical, agnosticism, devout, agnostic, christians | missiles, munitions, soviets, artillery, bunker, missile, explosives, tactical, grenades, soviet |
+| 8 | causes, metabolism, obstruction, bugging, xsession, disabling, debugger, behaviour, syndrome, occurs | prices, pricing, price, affordable, cheap, forsale, inexpensive, cost, purchases, priced |
+| 9 | xcreatewindow, programmable, bitmap, bitmaps, colormaps, freeware, gui, imagewriter, colormap, adobe | discrepancy, inaccuracies, defective, debacle, unrecognized, faulty, misconception, sceptical, refutation, warranted |
+
+## Package versions
+
+The model in this repo was trained using the following package versions:
+
+| Package | Version |
+| - | - |
+| scikit-learn | 1.3.2 |
+| sentence-transformers | 3.2.0 |
+| turftopic | 0.6.0 |
+| joblib | 1.2.0 |
+
+We recommend that you install the same, or compatible versions of these packages locally, before trying to load a model.
+

model.joblib

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+version https://git-lfs.github.com/spec/v1
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+size 145878291

package_versions.json

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+{"scikit-learn": "1.3.2", "sentence-transformers": "3.2.0", "turftopic": "0.6.0", "joblib": "1.2.0"}