metadata

tags:
  - setfit
  - sentence-transformers
  - text-classification
  - generated_from_setfit_trainer
widget:
  - text: >-
      Now let us conceive a particular volition, namely, the mode of thinking
      whereby the mind affirms, that the three interior angles of a triangle are
      equal to two right angles.
  - text: >-
      If we know beforehand what this state of affairs is, our desire is
      conscious; if not, unconscious.
  - text: 'The salvation of the soul in plain English: the world revolves around me.'
  - text: >-
      Masculine myths find their most seductive incarnation in the hetaera; more
      than any other woman, she is flesh and consciousness, idol, inspiration,
      muse; painters and sculptors want her as their model; she will nourish
      poets' dreams; it is in her that the intellectual will explore the
      treasures of feminine 'intuition'; she is more readily intelligent than
      the matron, because she is less set in hypocrisy.
  - text: " Since 2004, the Mandiant name has represented unparalleled security expertise, earning the trust of cyber security professionals and company executives across the world. By joining this unparalleled frontline experience with our industry leading, nation-state grade threat intelligence and innovative technology, we have ensured that FireEye knows more about current advanced threats than anyone. Today the world looks a lot different than it did in 2004. The cyber security industry has expanded (some might say exploded), but through all this change, one thing has remained the same: there is no substitute for world-class expertise and intelligence. With that in mind, we’ve continued to push the boundaries of innovation by expanding our expertise- and intelligence-backed solutions to stay ahead of market needs. Each is considered the gold standard in its respective space. These solutions include Mandiant Consulting, Mandiant Managed Defense, FireEye Threat Intelligence, FireEye Expertise On Demand, and Verodin Security Validation. Now, to streamline options and simplify the process of identifying solutions our customers need to proactively combat cyber threats, we are renaming our expertise- and intelligence-backed solutions to Mandiant, under the collective term Mandiant Solutions. The renaming of our solutions does not change pricing, content, or delivery today. Current subscribers of these services will continue to receive the same unparalleled frontline expertise they have come to rely on. As we move forward, the goal of Mandiant Solutions is to deliver synergies between these solutions to help customers improve security effectiveness by automating the security operations center and augmenting their security teams with Mandiant expertise and intelligence, regardless of the SIEM and security technology they have deployed.\_ Our Mandiant Solutions portfolio will include: Each of these offerings combines our technologies, intelligence and expertise, helping organizations meet evolving security challenges. Customers can be confident that Mandiant Solutions are backed by the industry’s best expertise and informed by the best threat intelligence available today.\_\_ For example, following the acquisition of Verodin last year, we’ve been actively integrating our market-leading threat intelligence with the industry’s most comprehensive security validation platform, now known as Mandiant Security Validation. This represents a significant benefit to our customers who can test and validate their organization’s readiness against the very latest techniques employed by today’s threat actors. Of course, our suite of enterprise solutions (FireEye Helix, Endpoint, Network, and Email Security) also benefits from and enhances this wealth of frontline expertise through our unique Innovation Cycle. It ensures that our products and services are able to learn and adapt to new threats faster and better than anyone.\_ As we look to the future, our vision is to continue to integrate these capabilities through a seamless, modern platform that accelerates our customers’ ability to measurably improve the people, processes, and technology they need to protect their critical assets.\_ Stay tuned for more updates as we rollout our renaming!\t\tSince 2004, the Mandiant name has represented unparalleled security expertise, earning the trust of cyber security professionals and company executives across the world. By joining this unparalleled frontline experience with our industry leading, nation-state grade threat intelligence and innovative technology, we have ensured that FireEye knows more about current advanced threats than anyone.Today the world looks a lot different than it did in 2004. The cyber security industry has expanded (some might say exploded), but through all this change, one thing has remained the same: there is no substitute for world-class expertise and intelligence.With that in mind, we’ve continued to push the boundaries of innovation by expanding our expertise- and intelligence-backed solutions to stay ahead of market needs. Each is considered the gold standard in its respective space. These solutions include Mandiant Consulting, Mandiant Managed Defense, FireEye Threat Intelligence, FireEye Expertise On Demand, and Verodin Security Validation.Now, to streamline options and simplify the process of identifying solutions our customers need to proactively combat cyber threats, we are renaming our expertise- and intelligence-backed solutions to Mandiant, under the collective term Mandiant Solutions.The renaming of our solutions does not change pricing, content, or delivery today. Current subscribers of these services will continue to receive the same unparalleled frontline expertise they have come to rely on.As we move forward, the goal of Mandiant Solutions is to deliver synergies between these solutions to help customers improve security effectiveness by automating the security operations center and augmenting their security teams with Mandiant expertise and intelligence, regardless of the SIEM and security technology they have deployed.\_Our Mandiant Solutions portfolio will include:Mandiant ConsultingMandiant Managed DefenseMandiant Threat IntelligenceMandiant Expertise On DemandMandiant Security Validation (formerly Verodin)Each of these offerings combines our technologies, intelligence and expertise, helping organizations meet evolving security challenges. Customers can be confident that Mandiant Solutions are backed by the industry’s best expertise and informed by the best threat intelligence available today.\_\_For example, following the acquisition of Verodin last year, we’ve been actively integrating our market-leading threat intelligence with the industry’s most comprehensive security validation platform, now known as Mandiant Security Validation. This represents a significant benefit to our customers who can test and validate their organization’s readiness against the very latest techniques employed by today’s threat actors.Of course, our suite of enterprise solutions (FireEye Helix, Endpoint, Network, and Email Security) also benefits from and enhances this wealth of frontline expertise through our unique Innovation Cycle. It ensures that our products and services are able to learn and adapt to new threats faster and better than anyone.\_As we look to the future, our vision is to continue to integrate these capabilities through a seamless, modern platform that accelerates our customers’ ability to measurably improve the people, processes, and technology they need to protect their critical assets.\_Stay tuned for more updates as we rollout our renaming!"
metrics:
  - accuracy
pipeline_tag: text-classification
library_name: setfit
inference: true
base_model: BAAI/bge-base-en-v1.5

SetFit with BAAI/bge-base-en-v1.5

This is a SetFit model that can be used for Text Classification. This SetFit model uses BAAI/bge-base-en-v1.5 as the Sentence Transformer embedding model. A LogisticRegression instance is used for classification.

The model has been trained using an efficient few-shot learning technique that involves:

Fine-tuning a Sentence Transformer with contrastive learning.
Training a classification head with features from the fine-tuned Sentence Transformer.

Model Details

Model Description

Model Type: SetFit
Sentence Transformer body: BAAI/bge-base-en-v1.5
Classification head: a LogisticRegression instance
Maximum Sequence Length: 512 tokens
Number of Classes: 2 classes

Model Sources

Repository: SetFit on GitHub
Paper: Efficient Few-Shot Learning Without Prompts
Blogpost: SetFit: Efficient Few-Shot Learning Without Prompts

Model Labels

Label Examples

cybersec

Label	Examples
cybersec	"cracking this password?. http://postimg.org/image/mi3xit477/\nit's Gargoyle Router Management Utility\ni'm a pre-beginner in cracking, i setted this up in my router, but i don't want to press the reset button, it took me a few weeks to do it, so i don't wanna re-install the firmware, but i forgot the password.....\ni have unlimited times of enter times, it's a 192.168.2.1\nhow can i crack it? i don't think it's encrypted though..." 'How can someone prevent a sybil attack when connecting through TOR?. As I understand it, running sybil BTC nodes through an anonymous network like TOR is much less expensive than in clearnet. This makes it possible that one could be connected to a majority of nodes controlled by the same entity, right? \n\n Is there any way to limit exposure to this when connection through TOR? \n\n ( I am asking for a friend :P ) \n' 'Added gigabit qos switch at workstation to work around 10/100 pass though in Cisco IP phone. Widows says the LAN connection is 1Gbps, but there is a cat5, not 5e going to the machine, am I really getting gigabit?. Windows 7.\nLong story short, the network connection to our PCs was running through our Cisco IP phones, which only supported 10/100. Per my IT guy, everything else on our network, the switches etc. can support gigabit, the phone is the choke point. To workaround, I got a 5 port gigabit switch, and put the phone on the high priority qos port. Under the LAN connection in control panel, it went from 100Mbps to 1Gbps.\nThe reason I am skeptical is that the ethernet cable from the switch to the PC is cat5, not 5e. My understanding is it needs to be 5e. Since there are 3 cables (wall to switch, switch to phone, switch to pc) per machine, I would rather not replace every cable on 17 machines.\nSo, if Windows says gigabit, is that all there is to it? Or should I run some type of diagnostic?\nLonger question, we have 20ish IP phones, and a server, sharing modestly sized documents, and some server-centric ERP type software. Do I even need the Gigabit speed? Some users I have switched are noticing some improvement, but we are not transferring huge files across the network regularly, so it may just seem anecdotally faster to them. How can I tell if I really need the extra bandwidth, and what I am using?\n\nI feel like a total idiot here, be gentle...\n\nThanks!'
non-cybersec	'Tex-shell in AUCTeX. Whenever I compile a file in AUCTeX (e.g. `C-c` `C-c` and then choosing an option) , it creates a buffer `tex-shell` where I can see the output of the compilation command. Once the compilation finishes this shell buffer stays open. What is the right way to close it? \n\n Besides showing me the compilation output, what else can I use it for? \n' 'Inserting a Creative Commons Licence into a LaTeX document. I'd like to insert a CC license on a manuscript (a book or report). I've seen the page for downloading the CC icons, and also some questions asked in the forum CC logo and Generate CC information. \n\n However, I do not get how to create the actual thing! \n\n Q: Can you please provide an example of a license info page (MWE)? That would be really helpful! \n' "Hey Reddit! We're Tritonal, and we just released our new U&Me album. Ask us anything!!. Yooo! What's up!? It's Dave & Chad of Tritonal, and we've just released our newest album, U&ME, available everywhere now! We're here to answer all of YOUR questions. Let's get this thing started!\n\nASK US ANYTHING! <3\n\nOur new album U&Me - https://enhanced.ffm.to/umealbum\nOur tour dates - http://tritonalmusic.com/shows\n\nProof: https://i.imgur.com/6cxJ9eU.jpg"

"cracking this password?. http://postimg.org/image/mi3xit477/\nit's Gargoyle Router Management Utility\ni'm a pre-beginner in cracking, i setted this up in my router, but i don't want to press the reset button, it took me a few weeks to do it, so i don't wanna re-install the firmware, but i forgot the password.....\ni have unlimited times of enter times, it's a 192.168.2.1\nhow can i crack it? i don't think it's encrypted though..."
'How can someone prevent a sybil attack when connecting through TOR?.
As I understand it, running sybil BTC nodes through an anonymous network like TOR is much less expensive than in clearnet. This makes it possible that one could be connected to a majority of nodes controlled by the same entity, right?
\n\n
Is there any way to limit exposure to this when connection through TOR?
\n\n
( I am asking for a friend :P )
\n'
'Added gigabit qos switch at workstation to work around 10/100 pass though in Cisco IP phone. Widows says the LAN connection is 1Gbps, but there is a cat5, not 5e going to the machine, am I really getting gigabit?. Windows 7.\nLong story short, the network connection to our PCs was running through our Cisco IP phones, which only supported 10/100. Per my IT guy, everything else on our network, the switches etc. can support gigabit, the phone is the choke point. To workaround, I got a 5 port gigabit switch, and put the phone on the high priority qos port. Under the LAN connection in control panel, it went from 100Mbps to 1Gbps.\nThe reason I am skeptical is that the ethernet cable from the switch to the PC is cat5, not 5e. My understanding is it needs to be 5e. Since there are 3 cables (wall to switch, switch to phone, switch to pc) per machine, I would rather not replace every cable on 17 machines.\nSo, if Windows says gigabit, is that all there is to it? Or should I run some type of diagnostic?\nLonger question, we have 20ish IP phones, and a server, sharing modestly sized documents, and some server-centric ERP type software. Do I even need the Gigabit speed? Some users I have switched are noticing some improvement, but we are not transferring huge files across the network regularly, so it may just seem anecdotally faster to them. How can I tell if I really need the extra bandwidth, and what I am using?\n\nI feel like a total idiot here, be gentle...\n\nThanks!'

non-cybersec

'Tex-shell in AUCTeX.
Whenever I compile a file in AUCTeX (e.g. C-c C-c and then choosing an option) , it creates a buffer tex-shell where I can see the output of the compilation command. Once the compilation finishes this shell buffer stays open. What is the right way to close it?
\n\n
Besides showing me the compilation output, what else can I use it for?
\n'
'Inserting a Creative Commons Licence into a LaTeX document.
I'd like to insert a CC license on a manuscript (a book or report). I've seen the page for downloading the CC icons, and also some questions asked in the forum CC logo and Generate CC information.
\n\n
However, I do not get how to create the actual thing!
\n\n
Q: Can you please provide an example of a license info page (MWE)? That would be really helpful!
\n'
"Hey Reddit! We're Tritonal, and we just released our new U&Me album. Ask us anything!!. Yooo! What's up!? It's Dave & Chad of Tritonal, and we've just released our newest album, U&ME, available everywhere now! We're here to answer all of YOUR questions. Let's get this thing started!\n\nASK US ANYTHING! <3\n\nOur new album U&Me - https://enhanced.ffm.to/umealbum\nOur tour dates - http://tritonalmusic.com/shows\n\nProof: https://i.imgur.com/6cxJ9eU.jpg"

Uses

Direct Use for Inference

First install the SetFit library:

pip install setfit

Then you can load this model and run inference.

from setfit import SetFitModel

# Download from the 🤗 Hub
model = SetFitModel.from_pretrained("naufalso/setfit-ctc-bge-base-en-v1.5")
# Run inference
preds = model("The salvation of the soul in plain English: the world revolves around me.")

Training Details

Training Set Metrics

Training set	Min	Median	Max
Word count	2	309.552	20280

Label	Training Sample Count
non-cybersec	1000
cybersec	1000

Training Hyperparameters

batch_size: (32, 32)
num_epochs: (1, 1)
max_steps: -1
sampling_strategy: oversampling
body_learning_rate: (2e-05, 1e-05)
head_learning_rate: 0.01
loss: CosineSimilarityLoss
distance_metric: cosine_distance
margin: 0.25
end_to_end: False
use_amp: False
warmup_proportion: 0.1
l2_weight: 0.01
seed: 42
eval_max_steps: -1
load_best_model_at_end: False

Training Results

Epoch	Step	Training Loss	Validation Loss
0.0000	1	0.2527	-
0.0008	50	0.2398	-
0.0016	100	0.2476	-
0.0024	150	0.2407	-
0.0032	200	0.2448	-
0.0040	250	0.241	-
0.0048	300	0.2381	-
0.0056	350	0.2345	-
0.0064	400	0.2344	-
0.0072	450	0.2284	-
0.0080	500	0.2232	-
0.0088	550	0.2167	-
0.0096	600	0.2082	-
0.0104	650	0.193	-
0.0112	700	0.163	-
0.0120	750	0.138	-
0.0128	800	0.1136	-
0.0136	850	0.0934	-
0.0144	900	0.0743	-
0.0152	950	0.0619	-
0.0160	1000	0.0455	-
0.0168	1050	0.0415	-
0.0176	1100	0.027	-
0.0184	1150	0.0276	-
0.0192	1200	0.0235	-
0.0200	1250	0.0183	-
0.0208	1300	0.0193	-
0.0216	1350	0.0161	-
0.0224	1400	0.0143	-
0.0232	1450	0.0134	-
0.0240	1500	0.0146	-
0.0248	1550	0.0152	-
0.0256	1600	0.0157	-
0.0264	1650	0.0138	-
0.0272	1700	0.0101	-
0.0280	1750	0.0089	-
0.0288	1800	0.0109	-
0.0296	1850	0.0122	-
0.0304	1900	0.0056	-
0.0312	1950	0.0094	-
0.0320	2000	0.0105	-
0.0328	2050	0.0101	-
0.0336	2100	0.0087	-
0.0344	2150	0.0089	-
0.0352	2200	0.0079	-
0.0360	2250	0.0091	-
0.0368	2300	0.0063	-
0.0376	2350	0.005	-
0.0384	2400	0.0083	-
0.0392	2450	0.0066	-
0.0400	2500	0.007	-
0.0408	2550	0.0049	-
0.0416	2600	0.0037	-
0.0424	2650	0.006	-
0.0432	2700	0.0063	-
0.0440	2750	0.0047	-
0.0448	2800	0.0062	-
0.0456	2850	0.0029	-
0.0464	2900	0.0038	-
0.0472	2950	0.0025	-
0.0480	3000	0.0021	-
0.0488	3050	0.0017	-
0.0496	3100	0.0041	-
0.0503	3150	0.0015	-
0.0511	3200	0.004	-
0.0519	3250	0.0019	-
0.0527	3300	0.005	-
0.0535	3350	0.0016	-
0.0543	3400	0.0037	-
0.0551	3450	0.0031	-
0.0559	3500	0.0024	-
0.0567	3550	0.0019	-
0.0575	3600	0.0036	-
0.0583	3650	0.0058	-
0.0591	3700	0.0024	-
0.0599	3750	0.0021	-
0.0607	3800	0.0015	-
0.0615	3850	0.0015	-
0.0623	3900	0.0016	-
0.0631	3950	0.0009	-
0.0639	4000	0.0014	-
0.0647	4050	0.0014	-
0.0655	4100	0.0021	-
0.0663	4150	0.0008	-
0.0671	4200	0.0031	-
0.0679	4250	0.0008	-
0.0687	4300	0.0025	-
0.0695	4350	0.0028	-
0.0703	4400	0.0025	-
0.0711	4450	0.0007	-
0.0719	4500	0.0018	-
0.0727	4550	0.0012	-
0.0735	4600	0.0012	-
0.0743	4650	0.0006	-
0.0751	4700	0.0006	-
0.0759	4750	0.0031	-
0.0767	4800	0.0017	-
0.0775	4850	0.0007	-
0.0783	4900	0.0011	-
0.0791	4950	0.0006	-
0.0799	5000	0.0006	-
0.0807	5050	0.0005	-
0.0815	5100	0.0005	-
0.0823	5150	0.0005	-
0.0831	5200	0.0005	-
0.0839	5250	0.0005	-
0.0847	5300	0.0005	-
0.0855	5350	0.0005	-
0.0863	5400	0.0005	-
0.0871	5450	0.0005	-
0.0879	5500	0.0004	-
0.0887	5550	0.0005	-
0.0895	5600	0.0004	-
0.0903	5650	0.0004	-
0.0911	5700	0.0004	-
0.0919	5750	0.0004	-
0.0927	5800	0.0004	-
0.0935	5850	0.0035	-
0.0943	5900	0.0112	-
0.0951	5950	0.0054	-
0.0959	6000	0.0058	-
0.0967	6050	0.0027	-
0.0975	6100	0.0051	-
0.0983	6150	0.0038	-
0.0991	6200	0.0031	-
0.0999	6250	0.0038	-
0.1007	6300	0.0021	-
0.1015	6350	0.0029	-
0.1023	6400	0.0018	-
0.1031	6450	0.0035	-
0.1039	6500	0.0017	-
0.1047	6550	0.0026	-
0.1055	6600	0.0016	-
0.1063	6650	0.0016	-
0.1071	6700	0.0004	-
0.1079	6750	0.001	-
0.1087	6800	0.0028	-
0.1095	6850	0.001	-
0.1103	6900	0.0003	-
0.1111	6950	0.001	-
0.1119	7000	0.0016	-
0.1127	7050	0.0003	-
0.1135	7100	0.0022	-
0.1143	7150	0.0022	-
0.1151	7200	0.0016	-
0.1159	7250	0.0007	-
0.1167	7300	0.0003	-
0.1175	7350	0.0006	-
0.1183	7400	0.0026	-
0.1191	7450	0.0004	-
0.1199	7500	0.0008	-
0.1207	7550	0.0004	-
0.1215	7600	0.0003	-
0.1223	7650	0.0004	-
0.1231	7700	0.0023	-
0.1239	7750	0.0004	-
0.1247	7800	0.0005	-
0.1255	7850	0.0005	-
0.1263	7900	0.0016	-
0.1271	7950	0.0005	-
0.1279	8000	0.0004	-
0.1287	8050	0.0003	-
0.1295	8100	0.0014	-
0.1303	8150	0.0052	-
0.1311	8200	0.005	-
0.1319	8250	0.0051	-
0.1327	8300	0.0009	-
0.1335	8350	0.0003	-
0.1343	8400	0.0004	-
0.1351	8450	0.0003	-
0.1359	8500	0.0003	-
0.1367	8550	0.0009	-
0.1375	8600	0.0003	-
0.1383	8650	0.0003	-
0.1391	8700	0.0003	-
0.1399	8750	0.0009	-
0.1407	8800	0.0012	-
0.1415	8850	0.0009	-
0.1423	8900	0.0003	-
0.1431	8950	0.0002	-
0.1439	9000	0.0002	-
0.1447	9050	0.0002	-
0.1455	9100	0.0002	-
0.1463	9150	0.0002	-
0.1471	9200	0.0002	-
0.1479	9250	0.0003	-
0.1487	9300	0.0002	-
0.1494	9350	0.0002	-
0.1502	9400	0.0002	-
0.1510	9450	0.0002	-
0.1518	9500	0.0002	-
0.1526	9550	0.0002	-
0.1534	9600	0.0002	-
0.1542	9650	0.0002	-
0.1550	9700	0.0002	-
0.1558	9750	0.0002	-
0.1566	9800	0.0002	-
0.1574	9850	0.0002	-
0.1582	9900	0.0002	-
0.1590	9950	0.0002	-
0.1598	10000	0.0002	-
0.1606	10050	0.0002	-
0.1614	10100	0.0002	-
0.1622	10150	0.0002	-
0.1630	10200	0.0002	-
0.1638	10250	0.0002	-
0.1646	10300	0.0002	-
0.1654	10350	0.0002	-
0.1662	10400	0.0002	-
0.1670	10450	0.0002	-
0.1678	10500	0.0002	-
0.1686	10550	0.0002	-
0.1694	10600	0.0002	-
0.1702	10650	0.0002	-
0.1710	10700	0.0002	-
0.1718	10750	0.0002	-
0.1726	10800	0.0002	-
0.1734	10850	0.0002	-
0.1742	10900	0.0002	-
0.1750	10950	0.0002	-
0.1758	11000	0.0002	-
0.1766	11050	0.0002	-
0.1774	11100	0.0002	-
0.1782	11150	0.0002	-
0.1790	11200	0.0002	-
0.1798	11250	0.0002	-
0.1806	11300	0.0002	-
0.1814	11350	0.0002	-
0.1822	11400	0.0002	-
0.1830	11450	0.0002	-
0.1838	11500	0.0002	-
0.1846	11550	0.0002	-
0.1854	11600	0.0002	-
0.1862	11650	0.0002	-
0.1870	11700	0.0002	-
0.1878	11750	0.0002	-
0.1886	11800	0.0001	-
0.1894	11850	0.0002	-
0.1902	11900	0.0002	-
0.1910	11950	0.0001	-
0.1918	12000	0.0001	-
0.1926	12050	0.0001	-
0.1934	12100	0.0001	-
0.1942	12150	0.0001	-
0.1950	12200	0.0001	-
0.1958	12250	0.0001	-
0.1966	12300	0.0001	-
0.1974	12350	0.0001	-
0.1982	12400	0.0001	-
0.1990	12450	0.0001	-
0.1998	12500	0.0001	-
0.2006	12550	0.0001	-
0.2014	12600	0.0001	-
0.2022	12650	0.0001	-
0.2030	12700	0.0001	-
0.2038	12750	0.0001	-
0.2046	12800	0.0001	-
0.2054	12850	0.0001	-
0.2062	12900	0.0001	-
0.2070	12950	0.0001	-
0.2078	13000	0.0001	-
0.2086	13050	0.0001	-
0.2094	13100	0.0001	-
0.2102	13150	0.0001	-
0.2110	13200	0.0001	-
0.2118	13250	0.0001	-
0.2126	13300	0.0001	-
0.2134	13350	0.0001	-
0.2142	13400	0.0001	-
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1.0	62563	-	0.0913

Framework Versions

Python: 3.12.7
SetFit: 1.1.0
Sentence Transformers: 3.3.1
Transformers: 4.47.0
PyTorch: 2.5.1+cu124
Datasets: 3.1.0
Tokenizers: 0.21.0

Citation

BibTeX

@article{https://doi.org/10.48550/arxiv.2209.11055,
    doi = {10.48550/ARXIV.2209.11055},
    url = {https://arxiv.org/abs/2209.11055},
    author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
    keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
    title = {Efficient Few-Shot Learning Without Prompts},
    publisher = {arXiv},
    year = {2022},
    copyright = {Creative Commons Attribution 4.0 International}
}