modelId stringlengths 4 81 | tags list | pipeline_tag stringclasses 17
values | config dict | downloads int64 0 59.7M | first_commit timestamp[ns, tz=UTC] | card stringlengths 51 438k | embedding list |
|---|---|---|---|---|---|---|---|
DoyyingFace/bert-asian-hate-tweets-concat-clean | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 25 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
t... | [
-0.013604359701275826,
-0.0011208804789930582,
-0.023518387228250504,
0.04503963515162468,
0.05708389729261398,
0.02039414830505848,
-0.029817121103405952,
-0.023884767666459084,
-0.047974687069654465,
0.05853741988539696,
0.036573003977537155,
-0.015278086997568607,
0.028265545144677162,
... |
albert-base-v2 | [
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 4,785,283 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_sa_GLUE_Experiment_data_aug_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
... | [
-0.014501247555017471,
-0.0021291300654411316,
-0.040973491966724396,
0.05281267315149307,
0.08422699570655823,
0.028186863288283348,
-0.01204255037009716,
-0.01997237280011177,
-0.044809963554143906,
0.07001393288373947,
0.02204362489283085,
-0.007097075693309307,
0.012226913124322891,
0.... |
albert-large-v2 | [
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 26,792 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_cola_256
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
... | [
-0.015233391895890236,
-0.0010183635167777538,
-0.02415686659514904,
0.04395100474357605,
0.05690953508019447,
0.02021734043955803,
-0.029123354703187943,
-0.023829812183976173,
-0.046385105699300766,
0.058691807091236115,
0.034803301095962524,
-0.016194520518183708,
0.028599265962839127,
... |
albert-xlarge-v1 | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 341 | 2023-02-01T23:00:57Z |
---
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
library_name: ultralytics
library_version: 8.0.25
inference: false
model-index:
- name: uisikdag/football_players_rf
results:
- task:
type: object-detection
metrics:
- type: precision # since mAP@0.... | [
0.0028509621042758226,
-0.01722399890422821,
0.02698863111436367,
0.01745961233973503,
0.042626749724149704,
0.0174893569201231,
-0.030380072072148323,
-0.015652664005756378,
-0.03641610965132713,
0.05291510373353958,
0.02465840056538582,
-0.0023045900743454695,
-0.0026128969620913267,
0.0... |
albert-xxlarge-v1 | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 7,091 | 2023-02-01T23:05:48Z | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert_sa_GLUE_Experiment_logit_kd_data_aug_cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
t... | [
-0.01451495848596096,
0.0057010226882994175,
-0.026744551956653595,
0.04892360791563988,
0.07158984988927841,
0.027548018842935562,
-0.023230010643601418,
-0.023990565910935402,
-0.049973174929618835,
0.06559931486845016,
0.038629330694675446,
-0.013615663163363934,
0.013467262499034405,
0... |
albert-xxlarge-v2 | [
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"exbert",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 42,640 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_cola_128
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
... | [
-0.015584951266646385,
-0.0002228087978437543,
-0.023829052224755287,
0.044373415410518646,
0.05655279755592346,
0.020571021363139153,
-0.030297379940748215,
-0.023910285905003548,
-0.046741925179958344,
0.05841907113790512,
0.03557893633842468,
-0.01689322106540203,
0.02858174964785576,
0... |
bert-base-cased-finetuned-mrpc | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 11,644 | 2023-02-01T23:17:09Z | ---
library_name: stable-baselines3
tags:
- PandaReachDense-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: PandaReachDense-v2
type: PandaReach... | [
-0.0500640869140625,
-0.016201360151171684,
-0.008638158440589905,
0.03632258251309395,
0.04077315703034401,
0.002863927511498332,
-0.02120320498943329,
-0.010843758471310139,
-0.037345509976148605,
0.05747208744287491,
0.025135179981589317,
-0.003583658952265978,
0.03146667778491974,
0.00... |
bert-base-chinese | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"zh",
"arxiv:1810.04805",
"transformers",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3,377,486 | 2023-02-01T23:25:15Z | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-CartPole-v1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type:... | [
-0.029234038665890694,
0.018230242654681206,
0.0036606306675821543,
0.009176405146718025,
0.04400138929486275,
-0.018997717648744583,
-0.021622145548462868,
-0.01578444615006447,
-0.029898816719651222,
0.0846094936132431,
0.017318837344646454,
-0.008446608670055866,
0.017369553446769714,
0... |
bert-base-multilingual-uncased | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"multilingual",
"af",
"sq",
"ar",
"an",
"hy",
"ast",
"az",
"ba",
"eu",
"bar",
"be",
"bn",
"inc",
"bs",
"br",
"bg",
"my",
"ca",
"ceb",
"ce",
"zh",
"cv",
"hr",
"cs",
"da",
"nl",
"en",
"et",
... | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 328,585 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: test_trainer
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# test_trainer
This mod... | [
-0.0224621519446373,
-0.014800110831856728,
-0.027959438040852547,
0.04538838565349579,
0.03659072145819664,
0.032405875623226166,
-0.0043147848919034,
-0.01722036488354206,
-0.042301516979932785,
0.05719926208257675,
0.03329775854945183,
-0.013995314948260784,
0.006841760594397783,
0.0403... |
bert-base-uncased | [
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"exbert",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 59,663,489 | 2023-02-01T23:34:44Z | ---
license: mit
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
datasets:
- huggan/selfie2anime
---
# This model is a fine-tuned diffusion model for unconditional image generation of animefaces.
Even after fine-tuning the diffusion model for 10 epochs the generated images are s... | [
0.006570412311702967,
-0.028227372094988823,
0.021396221593022346,
0.027111683040857315,
0.03376908227801323,
0.011160262860357761,
0.013064063154160976,
0.00009300410602008924,
-0.010062728077173233,
0.05172305181622505,
0.006053271237760782,
0.00794063787907362,
0.024120433256030083,
0.0... |
bert-large-cased-whole-word-masking | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 2,316 | 2023-02-01T23:37:08Z | ---
license: other
language:
- en
tags:
- art
- stable-diffuser-diffusers
- text-to-image
- stable-diffusion
library_name: diffusers
---
Hello, and welcome to our Osage Model based on andite/anything-v4.0 and Linaqruf/anything-v3.0.
This has been a work of [@rktfier](https://github.com/rktfier) **(Main Lead)**, [@f... | [
0.003237663535401225,
-0.03069702908396721,
0.007070932071655989,
0.01864556409418583,
0.03553934022784233,
-0.001124722883105278,
0.005067903082817793,
-0.006346222944557667,
-0.022357355803251266,
0.06107943132519722,
-0.003989765886217356,
-0.005759057588875294,
0.01907348819077015,
0.0... |
bert-large-uncased-whole-word-masking-finetuned-squad | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"question-answering",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | question-answering | {
"architectures": [
"BertForQuestionAnswering"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 480,510 | 2023-02-01T23:47:14Z | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: Churchill-GPT
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Churchill-GPT
This model is... | [
-0.025658562779426575,
0.005485521629452705,
-0.010785475373268127,
0.03974553570151329,
0.03797626867890358,
0.020602760836482048,
-0.010012824088335037,
0.012156522832810879,
-0.0496598482131958,
0.062277186661958694,
0.015443006530404091,
-0.020266981795430183,
0.008195057511329651,
0.0... |
bert-large-uncased-whole-word-masking | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 76,685 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: gl... | [
-0.01666845567524433,
0.002934709656983614,
-0.04185470566153526,
0.05229899287223816,
0.07893012464046478,
0.02982478402554989,
-0.007022865582257509,
-0.020362000912427902,
-0.047975942492485046,
0.0701044425368309,
0.026844479143619537,
-0.0175027959048748,
0.009678138419985771,
0.03311... |
bert-large-uncased | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 1,058,496 | 2023-02-01T23:55:25Z | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: mobilebert_sa_GLUE_Experiment_data_aug_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
... | [
-0.014776111580431461,
-0.007869558408856392,
-0.03578294813632965,
0.04649799317121506,
0.06476527452468872,
0.018818305805325508,
-0.019500037655234337,
-0.022784709930419922,
-0.04122479259967804,
0.06297259032726288,
0.02104933001101017,
-0.01008642092347145,
0.02859172783792019,
0.031... |
camembert-base | [
"pytorch",
"tf",
"safetensors",
"camembert",
"fill-mask",
"fr",
"dataset:oscar",
"arxiv:1911.03894",
"transformers",
"license:mit",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"CamembertForMaskedLM"
],
"model_type": "camembert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_... | 1,440,898 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-Pixelcopter-PLE-v0
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE... | [
-0.04013502597808838,
0.01548098586499691,
0.01421383861452341,
0.01738469861447811,
0.0492030531167984,
-0.013554353266954422,
-0.01945946365594864,
-0.023553557693958282,
-0.017467953264713287,
0.06766797602176666,
0.03537949547171593,
-0.008150936104357243,
0.011378075927495956,
-0.0072... |
distilbert-base-cased-distilled-squad | [
"pytorch",
"tf",
"rust",
"safetensors",
"openvino",
"distilbert",
"question-answering",
"en",
"dataset:squad",
"arxiv:1910.01108",
"arxiv:1910.09700",
"transformers",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"has_space"
] | question-answering | {
"architectures": [
"DistilBertForQuestionAnswering"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 257,745 | null | ---
license: odbl
language:
- es
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/mo... | [
-0.022236056625843048,
-0.016518788412213326,
-0.0038258822169154882,
0.026814959943294525,
0.034323226660490036,
0.041150469332933426,
-0.019720857962965965,
-0.022711480036377907,
-0.025545738637447357,
0.054612770676612854,
0.02530990168452263,
-0.015231727622449398,
0.02304496429860592,
... |
distilbert-base-german-cased | [
"pytorch",
"safetensors",
"distilbert",
"fill-mask",
"de",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repea... | 43,667 | null |
---
license: creativeml-openrail-m
base_model: stabilityai/stable-diffusion-2-1-base
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- lora
inference: true
---
# LoRA text2image fine-tuning - https://huggingface.co/romainlhardy/text2image-steatosis-512x512
These are LoRA adaption... | [
-0.004754600115120411,
-0.02424326352775097,
-0.006328829098492861,
0.023392053321003914,
0.03977253660559654,
-0.0021061913575977087,
-0.0024772894103080034,
-0.007139485329389572,
-0.022471453994512558,
0.04925379902124405,
-0.00027751619927585125,
-0.04045359045267105,
0.01775037311017513... |
distilbert-base-uncased-distilled-squad | [
"pytorch",
"tf",
"tflite",
"coreml",
"safetensors",
"distilbert",
"question-answering",
"en",
"dataset:squad",
"arxiv:1910.01108",
"arxiv:1910.09700",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | question-answering | {
"architectures": [
"DistilBertForQuestionAnswering"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 100,097 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: mobilebert_sa_GLUE_Experiment_data_aug_mrpc_256
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
... | [
-0.015931108966469765,
-0.00754949077963829,
-0.036505915224552155,
0.046049538999795914,
0.06529290974140167,
0.01895219087600708,
-0.01850179396569729,
-0.0222599059343338,
-0.040437038987874985,
0.06309980154037476,
0.020490650087594986,
-0.00988339725881815,
0.027983520179986954,
0.032... |
AKulk/wav2vec2-base-timit-epochs5 | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 4 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_rewa... | [
-0.029396209865808487,
0.019520889967679977,
0.006052189972251654,
0.01020913664251566,
0.04266488179564476,
-0.015512009151279926,
-0.026518672704696655,
-0.012444213032722473,
-0.028060775250196457,
0.08459777384996414,
0.01709902659058571,
-0.0030504039023071527,
0.01432698592543602,
0.... |
AdapterHub/roberta-base-pf-emo | [
"roberta",
"en",
"dataset:emo",
"arxiv:2104.08247",
"adapter-transformers",
"text-classification"
] | text-classification | {
"architectures": null,
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_... | 2 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SnowballTarget
library_name: ml-agents
---
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget** using... | [
-0.03244461119174957,
-0.0025829514488577843,
-0.019938934594392776,
0.05137093737721443,
0.0401417501270771,
0.026113353669643402,
-0.0017761894268915057,
-0.03599822148680687,
-0.02773018553853035,
0.04880530387163162,
0.023960955440998077,
-0.004700003191828728,
0.02018529362976551,
0.0... |
AdapterHub/roberta-base-pf-sick | [
"roberta",
"en",
"dataset:sick",
"arxiv:2104.08247",
"adapter-transformers",
"text-classification",
"adapterhub:nli/sick"
] | text-classification | {
"architectures": null,
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_... | 21 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
library_name: ml-agents
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Age... | [
-0.053727887570858,
0.006737678777426481,
-0.0060084667056798935,
0.05730888620018959,
0.026839952915906906,
0.028257666155695915,
-0.003510939422994852,
-0.03157204017043114,
-0.005735004786401987,
0.0492604598402977,
0.019222788512706757,
-0.012272495776414871,
0.008008256554603577,
0.02... |
AdapterHub/roberta-base-pf-social_i_qa | [
"roberta",
"en",
"dataset:social_i_qa",
"arxiv:2104.08247",
"adapter-transformers"
] | null | {
"architectures": null,
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_... | 4 | null | ---
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- tomekkorbak/detoxify-pile-chunk3-0-50000
- tomekkorbak/detoxify-pile-chunk3-50000-100000
- tomekkorbak/detoxify-pile-chunk3-100000-150000
- tomekkorbak/detoxify-pile-chunk3-150000-200000
- tomekkorbak/detoxify-pile-chunk3-200000-250000
- tomekko... | [
-0.00796584039926529,
-0.039861295372247696,
-0.020935583859682083,
0.013672241009771824,
0.04076392576098442,
0.025072399526834488,
-0.009637163020670414,
-0.0012835279339924455,
-0.034742143005132675,
0.06589392572641373,
0.01830139383673668,
-0.014861584641039371,
0.017111042514443398,
... |
Adharsh2608/DialoGPT-small-harrypotter | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | [
-0.039912149310112,
-0.014937307685613632,
-0.015878355130553246,
0.03603275120258331,
0.04769185557961464,
-0.006039220839738846,
-0.013294748030602932,
-0.024729955941438675,
-0.030654096975922585,
0.05469198897480965,
0.023091088980436325,
-0.033754169940948486,
0.018082601949572563,
0.... |
Akashpb13/Kabyle_xlsr | [
"pytorch",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"kab",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"sw",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"license:apache-... | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 3 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert_sa_GLUE_Experiment_data_aug_rte_96
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE RTE
type: glue
args... | [
-0.006563008762896061,
-0.00011112938955193385,
-0.03070017322897911,
0.04813966527581215,
0.08422888070344925,
0.02615310065448284,
-0.012668977491557598,
-0.020946530625224113,
-0.04921979829668999,
0.0683891624212265,
0.00971720740199089,
-0.020459366962313652,
0.010062125511467457,
0.0... |
AkshatSurolia/ICD-10-Code-Prediction | [
"pytorch",
"bert",
"transformers",
"text-classification",
"license:apache-2.0",
"has_space"
] | text-classification | {
"architectures": null,
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_bea... | 994 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-Pixelcopter-PLE-v0
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE... | [
-0.04020318761467934,
0.015934713184833527,
0.01435372419655323,
0.017239393666386604,
0.04914265125989914,
-0.013858136720955372,
-0.020171334967017174,
-0.02377844974398613,
-0.01772741600871086,
0.06801646202802658,
0.03534899652004242,
-0.00824025273323059,
0.011313171125948429,
-0.007... |
AlanDev/DallEMiniButBetter | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert_sa_GLUE_Experiment_logit_kd_data_aug_sst2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE SST2
type: glue
... | [
-0.009733717888593674,
-0.001238086842931807,
-0.039150021970272064,
0.049554046243429184,
0.07714825868606567,
0.03136146441102028,
-0.008215053007006645,
-0.021869760006666183,
-0.05217738822102547,
0.06974580138921738,
0.016751108691096306,
-0.01749322935938835,
0.013648778200149536,
0.... |
AlanDev/dall-e-better | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language:
- en
tags:
- medical
pipeline_tag: fill-mask
mask_token: "[MASK]"
widget:
- text: "This research study is studying a combination of drugs as a possible treatment for metastatic triple-negative [MASK] cancer."
example_title: "Trial Summary"
- text: "Participants must have histologically or cytologically ... | [
-0.0027026908937841654,
-0.025817498564720154,
0.006029839161783457,
0.04203316196799278,
0.05951923877000809,
0.01975248008966446,
-0.026208313181996346,
-0.014431025832891464,
-0.018629658967256546,
0.051146697252988815,
0.023504069074988365,
0.012636715546250343,
0.00981910154223442,
0.... |
Aleenbo/Arcane | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
widget:
- text: hdbglv
---
### sd-1-5-db-ai-creative-hub-hdbglv Dreambooth model trained by jaimexv with [Hugging Face Dreambooth Training Space](https://huggingface.co/spaces/multimodalart/dreambooth-training) with the v1-5 base model
You run your new concept v... | [
-0.03462919965386391,
-0.026141811162233353,
-0.019745854660868645,
0.031542424112558365,
0.023133492097258568,
0.025033866986632347,
-0.02833920158445835,
-0.028970954939723015,
-0.007398784160614014,
0.03949504345655441,
0.029880931600928307,
0.008738390170037746,
-0.027154019102454185,
... |
Aleksandar1932/gpt2-country | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | null | ---
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- tomekkorbak/detoxify-pile-chunk3-0-50000
- tomekkorbak/detoxify-pile-chunk3-50000-100000
- tomekkorbak/detoxify-pile-chunk3-100000-150000
- tomekkorbak/detoxify-pile-chunk3-150000-200000
- tomekkorbak/detoxify-pile-chunk3-200000-250000
- tomekko... | [
-0.00796584039926529,
-0.039861295372247696,
-0.020935583859682083,
0.013672241009771824,
0.04076392576098442,
0.025072399526834488,
-0.009637163020670414,
-0.0012835279339924455,
-0.034742143005132675,
0.06589392572641373,
0.01830139383673668,
-0.014861584641039371,
0.017111042514443398,
... |
Aleksandar1932/gpt2-hip-hop | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Cartpolev1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_rewar... | [
-0.030881786718964577,
0.016802920028567314,
0.003000871976837516,
0.009708775207400322,
0.04480942338705063,
-0.018287742510437965,
-0.02364230714738369,
-0.018704865127801895,
-0.030924981459975243,
0.08327724784612656,
0.017018403857946396,
-0.009239315055310726,
0.013918356038630009,
0... |
Aleksandar1932/gpt2-pop | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: distilbert_sa_GLUE_Experiment_data_aug_stsb_96
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
a... | [
-0.019769763574004173,
0.0000889348448254168,
-0.0541558600962162,
0.06091346964240074,
0.07863392680883408,
0.02327698841691017,
-0.01663857139647007,
-0.022031458094716072,
-0.05106557533144951,
0.06513089686632156,
0.007368014194071293,
-0.008125911466777325,
0.0010077941697090864,
0.02... |
Aleksandar1932/gpt2-soul | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
license: creativeml-openrail-m
tags:
- stable-diffusion
- text-to-image
---
# ◆RainierMix
- "RainierMix" is a merged model based on "ACertainThing".
---
# 《Notice》
- **"RainierMixV2" and "PastelRainier" are no longer available for commercial use due to a change in the license o... | [
-0.012509501539170742,
-0.026665521785616875,
-0.010181805118918419,
0.03280903398990631,
0.06324443221092224,
0.005124279763549566,
0.006811651401221752,
-0.009790708310902119,
-0.0372876338660717,
0.07164061069488525,
0.030595315620303154,
-0.023674461990594864,
-0.00882682204246521,
0.0... |
AlexKay/xlm-roberta-large-qa-multilingual-finedtuned-ru | [
"pytorch",
"xlm-roberta",
"question-answering",
"en",
"ru",
"multilingual",
"arxiv:1912.09723",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | question-answering | {
"architectures": [
"XLMRobertaForQuestionAnswering"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 10,012 | null | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: receipt_paper_invoice_document
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.6292135119438171
---
# rec... | [
-0.009960883297026157,
-0.014617150649428368,
0.0238092802464962,
0.030395565554499626,
0.016715148463845253,
-0.0010569221340119839,
-0.04072340577840805,
-0.01590333878993988,
-0.020624486729502678,
0.04592856392264366,
0.03931597247719765,
-0.002348110778257251,
0.011136792600154877,
0.... |
AlexMaclean/sentence-compression-roberta | [
"pytorch",
"roberta",
"token-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"RobertaForTokenClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_... | 13 | null | ---
language: en
license: mit
library_name: keras
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
# Model Details
## Model Description
<!-- Provide a longer summary of what this model is. -->
['Genome', 'Lighting', 'Hydrogen', 'Gene', 'Copper', 'Grape', 'Infrared', 'Ura... | [
-0.030117841437458992,
-0.0034778439439833164,
-0.005435569677501917,
0.03512158244848251,
0.05104614794254303,
0.02440270408987999,
-0.015323672443628311,
-0.015897011384367943,
-0.04252411797642708,
0.06659004092216492,
0.03431791439652443,
-0.027491573244333267,
0.03391110897064209,
0.0... |
AlexN/xls-r-300m-fr | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"model-index"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 17 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### GPRRPG Dreambooth model trained by rodrigobrand with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
Test the concept via A1111 Colab [... | [
-0.025624072179198265,
-0.008471881970763206,
-0.02282501570880413,
0.03347094729542732,
0.04577980935573578,
0.01680946722626686,
0.00414225785061717,
0.0030283196829259396,
-0.008205093443393707,
0.03272731602191925,
0.04928171634674072,
0.00024238531477749348,
-0.02547827735543251,
0.02... |
AlexeyIgnatov/albert-xlarge-v2-squad-v2 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language:
- uz
tags:
- transformers
- uzbek
widget:
---
<b>Use</b>
<pre><code class="language-python">from transformers import pipeline
fill_mask = pipeline(
"fill-mask",
model="Mansurbek/uz-syn-roberta"
)
fill_mask("Tadbirkorlik – foyda olish <mask> faoliyat.")
{'score': 0.17550185322761536,... | [
0.0082335090264678,
-0.038557201623916626,
-0.003857191652059555,
0.05496156960725784,
0.04650850594043732,
0.04741519317030907,
-0.009776967577636242,
0.0033224725630134344,
-0.05279754102230072,
0.08785922080278397,
0.01589440181851387,
-0.01938910223543644,
-0.005159241147339344,
0.0343... |
Alireza-rw/testbot | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SnowballTarget
library_name: ml-agents
---
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget** using... | [
-0.02999049611389637,
-0.0031428763177245855,
-0.018909523263573647,
0.0500798262655735,
0.03971516713500023,
0.025509843602776527,
-0.0017546485178172588,
-0.03581268712878227,
-0.028540631756186485,
0.048950374126434326,
0.021579178050160408,
-0.005037502385675907,
0.016850650310516357,
... |
Alireza1044/albert-base-v2-cola | [
"pytorch",
"tensorboard",
"albert",
"text-classification",
"en",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no... | 32 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
library_name: ml-agents
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra... | [
-0.04172368720173836,
-0.0009102188632823527,
-0.008547752164304256,
0.04904470965266228,
0.02826118841767311,
0.02273164689540863,
-0.027014724910259247,
-0.03722476586699486,
-0.005832907743752003,
0.0492069348692894,
0.0192024577409029,
-0.009852011688053608,
0.02005837857723236,
0.0307... |
Alireza1044/albert-base-v2-mnli | [
"pytorch",
"albert",
"text-classification",
"en",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no... | 235 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-Pixelcopter
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
... | [
-0.041238050907850266,
0.015366428531706333,
0.014930028468370438,
0.016922421753406525,
0.04919184371829033,
-0.013152179308235645,
-0.018994847312569618,
-0.023239469155669212,
-0.01697048731148243,
0.0683831050992012,
0.03613942861557007,
-0.0069634332321584225,
0.011812014505267143,
-0... |
Alireza1044/albert-base-v2-qnli | [
"pytorch",
"tensorboard",
"albert",
"text-classification",
"en",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no... | 41 | null | ---
library_name: stable-baselines3
tags:
- PandaReachDense-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: PandaReachDense-v2
type: PandaReach... | [
-0.04961695149540901,
-0.016144221648573875,
-0.008750725537538528,
0.036159101873636246,
0.041193556040525436,
0.0032875004690140486,
-0.02136012353003025,
-0.010455526411533356,
-0.038137417286634445,
0.05699886754155159,
0.024724645540118217,
-0.0031971228308975697,
0.031805381178855896,
... |
Alireza1044/albert-base-v2-qqp | [
"pytorch",
"albert",
"text-classification",
"en",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no... | 37 | null | ---
library_name: stable-baselines3
tags:
- PandaReachDense-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: PandaReachDense-v2
type: PandaReach... | [
-0.050130683928728104,
-0.01589304581284523,
-0.008795653469860554,
0.03632241114974022,
0.04085593670606613,
0.0029267945792526007,
-0.02150633931159973,
-0.010347723960876465,
-0.037919193506240845,
0.057001203298568726,
0.024658694863319397,
-0.003099572379142046,
0.03166394680738449,
0... |
Alireza1044/albert-base-v2-rte | [
"pytorch",
"tensorboard",
"albert",
"text-classification",
"en",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no... | 30 | null | ---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: huynhdoo/distilcamembert-base-finetuned-CLS
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
... | [
-0.04711966589093208,
-0.0016607632860541344,
0.002673431998118758,
0.012603259645402431,
0.02640523947775364,
0.01669713482260704,
-0.01590484008193016,
-0.00355444080196321,
-0.03550908342003822,
0.052898138761520386,
0.022698991000652313,
-0.02940557524561882,
0.0005670231766998768,
0.0... |
Alireza1044/dwight_bert_lm | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 14 | null | ---
library_name: stable-baselines3
tags:
- AntBulletEnv-v0
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: AntBulletEnv-v0
type: AntBulletEnv-v0
... | [
-0.045688025653362274,
-0.0005450178869068623,
-0.022301102057099342,
0.032290514558553696,
0.043666914105415344,
0.0178899597376585,
-0.017853979021310806,
-0.030861150473356247,
-0.037762824445962906,
0.06912325322628021,
0.022278187796473503,
0.0033324211835861206,
0.015215727500617504,
... |
Aliskin/xlm-roberta-base-finetuned-marc | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
library_name: ml-agents
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Age... | [
-0.04966333135962486,
0.007578176446259022,
-0.006953476928174496,
0.05904965102672577,
0.027098551392555237,
0.03147748485207558,
-0.002528261858969927,
-0.035277359187603,
-0.004178614355623722,
0.051811229437589645,
0.017409080639481544,
-0.012051454745233059,
0.007480588275939226,
0.02... |
Alvenir/wav2vec2-base-da | [
"pytorch",
"wav2vec2",
"pretraining",
"da",
"transformers",
"speech",
"license:apache-2.0"
] | null | {
"architectures": [
"Wav2Vec2ForPreTraining"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 62 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: my_awesome_model
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then ... | [
-0.03357655182480812,
-0.008589978329837322,
-0.01008489541709423,
0.03277166932821274,
0.022257637232542038,
0.020998168736696243,
-0.0050487397238612175,
-0.018170133233070374,
-0.042872849851846695,
0.07650168985128403,
0.04168076813220978,
-0.014144361950457096,
-0.0009834876982495189,
... |
Amalq/distilroberta-base-finetuned-MentalHealth | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: juliietth/mt5-small-finetuned-amazon-en-es
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment... | [
-0.039627138525247574,
-0.007336918730288744,
0.015898533165454865,
0.01394884567707777,
0.030273105949163437,
0.005436384584754705,
-0.024283630773425102,
-0.007673385087400675,
-0.03582394868135452,
0.05384688824415207,
0.024274880066514015,
-0.025220705196261406,
0.013156049884855747,
0... |
Amrrs/south-indian-foods | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index",
"autotrain_compatible"
] | image-classification | {
"architectures": [
"ViTForImageClassification"
],
"model_type": "vit",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 21 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### StableDiffusion_finetuning_cat_emoticon_style Dreambooth model trained by jha2ee with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
T... | [
-0.03073994442820549,
-0.01817665994167328,
-0.016767963767051697,
0.0360751748085022,
0.027225181460380554,
0.015339397825300694,
-0.0011181459994986653,
-0.004602186847478151,
-0.015109725296497345,
0.03657800704240799,
0.019169429317116737,
-0.009914555586874485,
-0.005270136520266533,
... |
Anders/itu-ams-summa | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### tfmfurbase-v1.1 Dreambooth model trained by Deitsao with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
Test the concept via A1111 Col... | [
-0.027037283405661583,
-0.01581934466958046,
-0.02713179774582386,
0.03572578728199005,
0.02834569849073887,
0.024428706616163254,
0.007670119870454073,
-0.0020616152323782444,
-0.014303077012300491,
0.02996249310672283,
0.03738979622721672,
0.006553406361490488,
-0.023168403655290604,
0.0... |
Andi/bert-tt-ner-1 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... | [
-0.03735543414950371,
-0.002701518824324012,
-0.005745241418480873,
0.02594962902367115,
0.046146735548973083,
-0.021115900948643684,
-0.005432005971670151,
-0.028300920501351357,
-0.032852184027433395,
0.06635703146457672,
0.03246353194117546,
-0.02358991838991642,
0.023271771147847176,
0... |
Andranik/TestPytorchClassification | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 36 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... | [
-0.018401620909571648,
-0.016988251358270645,
-0.006017525680363178,
0.029507722705602646,
0.05127638950943947,
-0.018746687099337578,
-0.010276571847498417,
-0.008799382485449314,
-0.060123100876808167,
0.05389638990163803,
-0.0029915340710431337,
-0.009768789634108543,
0.02572932466864586,... |
Andrey78/my_nlp_test_model | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language:
- rw
pipeline_tag: text-to-speech
---
## Model Description
<!-- Provide a longer summary of what this model is. -->
This model is an end-to-end deep-learning-based Kinyarwanda Text-to-Speech (TTS). Due to its zero-shot learning capabilities, new voices can be introduced with 1min speech.
The model was... | [
-0.026528123766183853,
-0.024856287986040115,
-0.015031126327812672,
0.02801879681646824,
0.06417982280254364,
0.02855740301311016,
0.0022862344048917294,
-0.00771331274881959,
-0.021315131336450577,
0.049620192497968674,
0.01965288631618023,
-0.021494809538125992,
0.00875211600214243,
0.0... |
AndyyyCai/bert-base-uncased-finetuned-copa | [
"pytorch",
"bert",
"multiple-choice",
"transformers"
] | multiple-choice | {
"architectures": [
"BertForMultipleChoice"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 4 | null | ---
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: speller-t5-90
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# speller-t5-90
This mode... | [
-0.012665310874581337,
-0.011124351061880589,
-0.007834346033632755,
0.04342792555689812,
0.04378822073340416,
0.009335467591881752,
-0.0223949383944273,
-0.016488533467054367,
-0.06361903995275497,
0.04440615698695183,
0.012414509430527687,
-0.03265867382287979,
-0.010294049046933651,
0.0... |
AnonymousSub/AR_rule_based_roberta_bert_triplet_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: test_glue
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# test_glue
This model is a fine-... | [
-0.02987186424434185,
-0.028991125524044037,
-0.009274695068597794,
0.04679172486066818,
0.04719996824860573,
0.024991601705551147,
0.0006855425890535116,
-0.008252467028796673,
-0.061346717178821564,
0.05050277337431908,
0.0176637452095747,
-0.012347294948995113,
0.02102213352918625,
0.03... |
AnonymousSub/AR_rule_based_roberta_hier_triplet_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 4 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... | [
-0.0371953584253788,
-0.002923623425886035,
-0.005562846548855305,
0.02602737583220005,
0.04615321755409241,
-0.021196866407990456,
-0.0057583097368478775,
-0.027780771255493164,
-0.032788533717393875,
0.06655804067850113,
0.032090041786432266,
-0.0237454604357481,
0.023005275055766106,
0.... |
AnonymousSub/SR_rule_based_roberta_hier_quadruplet_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 5 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: mobilebert_sa_GLUE_Experiment_data_aug_sst2_256
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE SST2
type: glue
a... | [
-0.013332285918295383,
-0.009437714703381062,
-0.033988118171691895,
0.04629886895418167,
0.06457030773162842,
0.018424129113554955,
-0.018955131992697716,
-0.021845536306500435,
-0.04244697466492653,
0.06321420520544052,
0.013324287720024586,
-0.010426743887364864,
0.02885100618004799,
0.... |
AnonymousSub/consert-s10-AR | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 31 | null | ---
language:
- ja
- de
- ru
tags:
- kenlm
- perplexity
- n-gram
- kneser-ney
- bigscience
license: mit
datasets:
- wikipedia
---
# KenLM models
This repo contains several KenLM models trained on different tokenized datasets and languages.
KenLM models are probabilistic n-gram languge models that models. One use cas... | [
0.007714416831731796,
-0.03638378903269768,
-0.009674981236457825,
0.05170296132564545,
0.028204089030623436,
0.02742920257151127,
-0.005968831479549408,
0.004859239794313908,
-0.03841995820403099,
0.06883476674556732,
0.028240466490387917,
-0.0065310196951031685,
0.00758189195767045,
0.03... |
AnonymousSub/consert-s10-SR | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 28 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: my_awesome_qa_model
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_awesome_qa_m... | [
-0.03130201995372772,
-0.018975786864757538,
-0.006530738435685635,
0.037415385246276855,
0.03359980508685112,
0.003605393460020423,
-0.003234975039958954,
-0.011170465499162674,
-0.03936516121029854,
0.05617254227399826,
0.007635046727955341,
-0.002271363977342844,
0.0011623947648331523,
... |
AnonymousSub/declutr-model | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 4 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... | [
-0.01937737688422203,
-0.017312344163656235,
-0.006513836327940226,
0.034090522676706314,
0.0504600964486599,
-0.019629033282399178,
-0.012295974418520927,
-0.013399787247180939,
-0.06025348976254463,
0.05684560909867287,
-0.004707325715571642,
-0.012535277754068375,
0.021054375916719437,
... |
AnonymousSub/dummy_2_parent | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 3 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert_sa_GLUE_Experiment_logit_kd_data_aug_wnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE WNLI
type: glue
... | [
-0.021007908508181572,
-0.002914338605478406,
-0.032416630536317825,
0.05377153307199478,
0.0740862712264061,
0.03125448897480965,
-0.002867896342650056,
-0.026672208681702614,
-0.04300297424197197,
0.07017046213150024,
0.027932021766901016,
-0.021277716383337975,
0.001665834104642272,
0.0... |
AnonymousSub/roberta-base_squad2.0 | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 6 | null |
---
license: cc-by-4.0
metrics:
- bleu4
- meteor
- rouge-l
- bertscore
- moverscore
language: de
datasets:
- lmqg/qg_dequad
pipeline_tag: text2text-generation
tags:
- question generation
- answer extraction
widget:
- text: "generate question: Empfangs- und Sendeantenne sollen in ihrer Polarisation übereinstimmen, ande... | [
0.036781951785087585,
-0.01132310088723898,
-0.03056015819311142,
0.021042877808213234,
0.041470903903245926,
0.004734280984848738,
-0.007795447017997503,
0.013743976131081581,
-0.06265036761760712,
0.06022663414478302,
0.04325519874691963,
-0.009940099902451038,
-0.016913890838623047,
0.0... |
AnonymousSub/rule_based_bert_quadruplet_epochs_1_shard_1_wikiqa | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 33 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-custom-colab
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
... | [
-0.029994089156389236,
-0.0020363633520901203,
-0.011652424931526184,
0.02890762686729431,
0.03548804298043251,
0.013299169018864632,
-0.020033739507198334,
0.004629051312804222,
-0.02977544069290161,
0.04490785300731659,
0.02664361335337162,
-0.016216978430747986,
0.0037596048787236214,
0... |
AnonymousSub/rule_based_bert_triplet_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 8 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SoccerTwos
library_name: ml-agents
---
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos** using the [Unit... | [
-0.020385829731822014,
-0.004944799467921257,
0.010357232764363289,
0.03825311362743378,
0.032755669206380844,
0.013329620473086834,
-0.029400231316685677,
-0.015955127775669098,
-0.016271835193037987,
0.061330780386924744,
0.00842120498418808,
-0.0005381727823987603,
0.010047337040305138,
... |
AnonymousSub/rule_based_hier_quadruplet_0.1_epochs_1_shard_1_squad2.0 | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"BertForQuestionAnswering"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 4 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
config: default
split:... | [
-0.009148849174380302,
-0.007459684275090694,
0.010330176912248135,
0.03704231604933739,
0.03377451002597809,
0.0027385950088500977,
-0.03262439742684364,
-0.02975311689078808,
-0.027801210060715675,
0.05110039934515953,
0.02040061540901661,
-0.01567513309419155,
-0.008526301942765713,
0.0... |
AnonymousSub/rule_based_hier_triplet_epochs_1_shard_10 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 8 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... | [
-0.037604428827762604,
-0.002828367054462433,
-0.005161268170922995,
0.025461815297603607,
0.04563189297914505,
-0.021528059616684914,
-0.005408715922385454,
-0.027662580832839012,
-0.03288896754384041,
0.06671638041734695,
0.0321478508412838,
-0.023508882150053978,
0.022778719663619995,
0... |
AnonymousSub/rule_based_hier_triplet_epochs_1_shard_1_squad2.0 | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"BertForQuestionAnswering"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 2 | null | ---
tags:
- spacy
language:
- en
model-index:
- name: en_ml_pipeline_mldata
results: []
---
| Feature | Description |
| --- | --- |
| **Name** | `en_ml_pipeline_mldata` |
| **Version** | `0.0.0` |
| **spaCy** | `>=3.4.4,<3.5.0` |
| **Default Pipeline** | `tok2vec`, `transformer`, `dual` |
| **Components** | `tok2vec`... | [
-0.0060114567168056965,
-0.0046804905869066715,
-0.01827949285507202,
0.03456834331154823,
0.06105690822005272,
0.014284158125519753,
-0.009294607676565647,
0.0002756771573331207,
-0.04356071352958679,
0.05553025007247925,
0.030469276010990143,
-0.011437694542109966,
0.003014597576111555,
... |
AnonymousSub/rule_based_hier_triplet_epochs_1_shard_1_wikiqa_copy | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 1 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: pixcelcopter-v1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
metri... | [
-0.04155467450618744,
0.013348222710192204,
0.015800857916474342,
0.0179641991853714,
0.047933176159858704,
-0.01169018168002367,
-0.01790706068277359,
-0.02987510710954666,
-0.018003322184085846,
0.06630437076091766,
0.037456050515174866,
-0.005375191103667021,
0.006699077319353819,
-0.00... |
AnonymousSub/rule_based_only_classfn_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 4 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
widget:
- text: vskiy1
---
### Visual Kei Part Two Dreambooth model trained by Duskfallcrew with [Hugging Face Dreambooth Training Space](https://huggingface.co/spaces/multimodalart/dreambooth-training) with the v1-5 base model
You run your new concept via `diff... | [
-0.06052512302994728,
-0.029516713693737984,
-0.005513947922736406,
0.01878206618130207,
0.0375451035797596,
0.011997120454907417,
-0.01966903544962406,
-0.007982584647834301,
-0.03224536404013634,
0.05269589275121689,
0.052195437252521515,
0.028010303154587746,
-0.013751576654613018,
0.03... |
AnonymousSub/rule_based_only_classfn_epochs_1_shard_10 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 7 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... | [
-0.01917916163802147,
-0.01828896626830101,
-0.007343933451920748,
0.0342872217297554,
0.05078543350100517,
-0.018563754856586456,
-0.013229859061539173,
-0.012634935788810253,
-0.06048611178994179,
0.05662114545702934,
-0.005117566790431738,
-0.011355971917510033,
0.020748890936374664,
0.... |
AnonymousSub/rule_based_only_classfn_epochs_1_shard_1_squad2.0 | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"BertForQuestionAnswering"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 2 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-Taxi-v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.50 +/- 2.76... | [
-0.02184537798166275,
-0.016798628494143486,
-0.009381482377648354,
0.03014380671083927,
0.04782678559422493,
-0.0003381903807166964,
-0.019196562469005585,
0.0019634978380054235,
-0.04005120322108269,
0.055623915046453476,
0.012608163058757782,
-0.010786731727421284,
0.009113561362028122,
... |
AnonymousSub/rule_based_only_classfn_twostage_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 10 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SoccerTwos
library_name: ml-agents
---
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos** using the [Unit... | [
-0.022356629371643066,
-0.0058798352256417274,
0.01013843435794115,
0.039495859295129776,
0.03267320990562439,
0.01567447930574417,
-0.029988648369908333,
-0.01618279330432415,
-0.017001254484057426,
0.06163408234715462,
0.006503966171294451,
0.0010472401045262814,
0.011500158347189426,
0.... |
AnonymousSub/rule_based_only_classfn_twostage_epochs_1_shard_1_wikiqa | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 27 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: pixelcopter_policy_230203
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0... | [
-0.03743531554937363,
0.012585300952196121,
0.014750007539987564,
0.02101832814514637,
0.048387426882982254,
-0.010421649552881718,
-0.019184213131666183,
-0.029984742403030396,
-0.013897924683988094,
0.06091545149683952,
0.03567434474825859,
-0.011033518239855766,
0.008719800971448421,
-0... |
AnonymousSub/rule_based_roberta_bert_quadruplet_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | null | 使用https://github.com/k2-fsa/sherpa-ncnn的模型，这里是对旧版本的一个转存，后续将同步更新到新版本 | [
-0.05054180696606636,
-0.03335602581501007,
0.019723063334822655,
0.020801151171326637,
0.048639681190252304,
-0.01138642244040966,
-0.006962672341614962,
0.016463257372379303,
-0.06299234926700592,
0.042751166969537735,
0.010603661648929119,
0.02120225504040718,
0.03327174484729767,
0.025... |
AnonymousSub/rule_based_roberta_bert_quadruplet_epochs_1_shard_1_wikiqa | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 23 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like cluste... | [
-0.03682786226272583,
-0.017038146033883095,
-0.016540275886654854,
0.0510595329105854,
0.01117929257452488,
0.04447409510612488,
-0.01840854622423649,
-0.002739659510552883,
-0.070090651512146,
0.08364398777484894,
0.03946809098124504,
0.013144438154995441,
0.00234610796906054,
0.04092745... |
AnonymousSub/rule_based_roberta_bert_triplet_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 2 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like cluste... | [
-0.03632119297981262,
-0.01704941876232624,
-0.017162278294563293,
0.05106724053621292,
0.01151119265705347,
0.04437613859772682,
-0.018663978204131126,
-0.0026771770790219307,
-0.0695725753903389,
0.08319412916898727,
0.03939869627356529,
0.012617562897503376,
0.0022086689714342356,
0.040... |
AnonymousSub/rule_based_roberta_bert_triplet_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 2 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
library_name: ml-agents
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra... | [
-0.04026215150952339,
-0.002480198862031102,
-0.007867706939578056,
0.05011169612407684,
0.028552163392305374,
0.021959735080599785,
-0.02573617547750473,
-0.03746069222688675,
-0.005425397772341967,
0.04953038692474365,
0.019542735069990158,
-0.009494856931269169,
0.020218780264258385,
0.... |
AnonymousSub/rule_based_roberta_bert_triplet_epochs_1_shard_1_squad2.0 | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 3 | null | ---
library_name: paddlenlp
---
# sijunhe/tiny-random-stable-diffusion-pipe-1 | [
-0.03616978973150253,
-0.004685654304921627,
0.0013647997984662652,
0.025053344666957855,
0.037037771195173264,
-0.013592264614999294,
0.027226198464632034,
0.020706906914711,
-0.04926586151123047,
0.03940865024924278,
0.015656528994441032,
0.00786830484867096,
0.027317997068166733,
0.0418... |
AnonymousSub/rule_based_roberta_hier_triplet_epochs_1_shard_1_wikiqa_copy | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 2 | null | ---
license: cc-by-4.0
tags:
- generated_from_keras_callback
model-index:
- name: leorena/traductor-en-es
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# leorena/tra... | [
-0.02577296830713749,
-0.02333892323076725,
0.013179153203964233,
0.032409217208623886,
0.03880276903510094,
-0.0003824189770966768,
-0.008577056229114532,
-0.017779802903532982,
-0.04888325557112694,
0.047046173363924026,
-0.00585028063505888,
-0.030936826020479202,
0.012907274067401886,
... |
AnonymousSub/rule_based_roberta_only_classfn_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
datasets:
- relbert/semeval2012_relational_similarity
model-index:
- name: relbert/relbert-roberta-large-nce-a-semeval2012
results:
- task:
name: Relation Mapping
type: sorting-task
dataset:
name: Relation Mapping
args: relbert/relation_mapping
type: relation-mapping
metric... | [
0.00438268668949604,
-0.007298431824892759,
-0.02526775933802128,
0.05468612536787987,
0.04555201530456543,
0.026333671063184738,
-0.033138200640678406,
-0.009839043021202087,
-0.06834151595830917,
0.028514157980680466,
0.014090027660131454,
0.004516839515417814,
0.018149038776755333,
0.03... |
AnonymousSub/rule_based_roberta_only_classfn_epochs_1_shard_1_wikiqa | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 27 | null | ---
datasets:
- relbert/semeval2012_relational_similarity
model-index:
- name: relbert/relbert-roberta-large-nce-c-semeval2012
results:
- task:
name: Relation Mapping
type: sorting-task
dataset:
name: Relation Mapping
args: relbert/relation_mapping
type: relation-mapping
metric... | [
0.005898726172745228,
-0.00819365680217743,
-0.026023361831903458,
0.05484003573656082,
0.04542166367173195,
0.027708761394023895,
-0.03266853839159012,
-0.00924691278487444,
-0.06966601312160492,
0.02945721335709095,
0.013687060214579105,
0.0038920294027775526,
0.01844952628016472,
0.0321... |
AnonymousSub/rule_based_roberta_only_classfn_twostage_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
license: mit
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
---
# Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
This model is a diffusion model for unconditional image generation of butts.
## Usage
```python... | [
-0.008664372377097607,
-0.016448719426989555,
0.0040403264574706554,
0.027726441621780396,
0.02012508735060692,
0.02690690942108631,
0.008649615570902824,
-0.013332247734069824,
-0.010247420519590378,
0.048942916095256805,
0.00789780542254448,
-0.007336257956922054,
0.028896452859044075,
0... |
AnonymousSub/rule_based_roberta_only_classfn_twostage_epochs_1_shard_1_squad2.0 | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 2 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-CartPole-v1
results:
- metrics:
- type: mean_reward
value: 500.00 +/- 0.00
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-lear... | [
-0.029124854132533073,
0.02070334181189537,
0.004933652933686972,
0.008644809015095234,
0.0441809706389904,
-0.018566491082310677,
-0.022240586578845978,
-0.018317775800824165,
-0.032727982848882675,
0.08469977974891663,
0.018964925780892372,
-0.011117657646536827,
0.017095237970352173,
0.... |
AnonymousSub/rule_based_roberta_only_classfn_twostage_epochs_1_shard_1_wikiqa | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 24 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- go_emotions
metrics:
- f1
- accuracy
model-index:
- name: bert-base-goemotions
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: go_emotions
type: go_emotions
config: simplified
... | [
-0.023741718381643295,
-0.0002791041333694011,
-0.014308135956525803,
0.0310147013515234,
0.048174887895584106,
0.01857200637459755,
-0.012183435261249542,
-0.03598715737462044,
-0.023813476786017418,
0.04502756521105766,
0.0057490309700369835,
-0.04118857905268669,
0.028311092406511307,
0... |
AnonymousSub/rule_based_roberta_twostagequadruplet_hier_epochs_1_shard_1_squad2.0 | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 2 | null | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: receipt_paper_invoice_documentv2
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.6339285969734192
---
# r... | [
-0.008652563206851482,
-0.018141038715839386,
0.02260608598589897,
0.03154686838388443,
0.017372891306877136,
-0.0008048495510593057,
-0.03892650082707405,
-0.016220664605498314,
-0.02180992066860199,
0.045705802738666534,
0.041113097220659256,
-0.002375079318881035,
0.011130547150969505,
... |
AnonymousSub/rule_based_roberta_twostagetriplet_hier_epochs_1_shard_1_squad2.0 | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: mini-distilbert-finetuned-gest-pred
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and... | [
0.0020793091971427202,
0.014181140810251236,
-0.009154443629086018,
0.025710755959153175,
0.047355908900499344,
0.02574397809803486,
-0.022239139303565025,
-0.007812694646418095,
-0.04670562967658043,
0.05920496582984924,
0.0198668222874403,
-0.03186294436454773,
0.02288908138871193,
0.033... |
AnonymousSub/specter-bert-model_copy_wikiqa | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 26 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SoccerTwos
library_name: ml-agents
---
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos** using the [Unit... | [
-0.019575051963329315,
-0.0066060349345207214,
0.007689968217164278,
0.03208852931857109,
0.029914606362581253,
0.011751284822821617,
-0.021151527762413025,
-0.012156510725617409,
-0.016407888382673264,
0.06132711097598076,
0.015429116785526276,
0.0021237959153950214,
0.00712173618376255,
... |
AnonymousSub/unsup-consert-base_squad2.0 | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"BertForQuestionAnswering"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 2 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### Galverse-Diffusion-wf-8888 Dreambooth model trained by jarvissan with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
Test the concept ... | [
-0.019619571045041084,
-0.03173178806900978,
-0.007314630784094334,
0.03973899781703949,
0.03469536453485489,
0.02356823906302452,
0.011859029531478882,
-0.014196988195180893,
-0.006183810997754335,
0.024123944342136383,
0.04657146707177162,
0.006673373747617006,
0.010587082244455814,
0.03... |
AnonymousSub/unsup-consert-papers | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 2 | null | ---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4... | [
0.007429787423461676,
-0.034975919872522354,
0.00044122387771494687,
0.04189398139715195,
0.04622026905417442,
0.013660196214914322,
-0.023083165287971497,
-0.00889843050390482,
-0.03562261164188385,
0.037559229880571365,
-0.005842221435159445,
-0.005967587232589722,
0.0013576119672507048,
... |
AnonymousSubmission/pretrained-model-1 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-CartPole-V1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type:... | [
-0.029651306569576263,
0.01819695346057415,
0.003343591932207346,
0.009046057239174843,
0.044131141155958176,
-0.019345706328749657,
-0.021295860409736633,
-0.01570025272667408,
-0.02982334978878498,
0.08448690176010132,
0.017289811745285988,
-0.008545351214706898,
0.01760176382958889,
0.0... |
Anthos23/sentiment-roberta-large-english-finetuned-sentiment-analysis | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/a_nnaschneider/1675427059055/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; ... | [
-0.0022896018344908953,
-0.03906789422035217,
0.0010683945147320628,
0.0553550124168396,
0.047831904143095016,
0.009681825526058674,
-0.01736338995397091,
-0.012552818283438683,
-0.04979851096868515,
0.03545433282852173,
0.011265876702964306,
-0.002859819447621703,
-0.008848432451486588,
0... |
Antony/mint_model | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
---
# Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
This model is a diffusion model for unconditional image generation of butts.
## Usage
```python... | [
-0.00880465004593134,
-0.016497990116477013,
0.003926627337932587,
0.02749677747488022,
0.019911983981728554,
0.027210593223571777,
0.008032983168959618,
-0.013053561560809612,
-0.010747214779257774,
0.04942912980914116,
0.007481361273676157,
-0.007521247956901789,
0.02930271252989769,
0.0... |
Anubhav23/IndianlegalBert | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
library_name: ml-agents
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Age... | [
-0.05048944428563118,
0.007841089740395546,
-0.007864858955144882,
0.058405663818120956,
0.028275558724999428,
0.03159455582499504,
-0.003960677422583103,
-0.034817010164260864,
-0.004131513647735119,
0.052429333329200745,
0.01853899657726288,
-0.014033078216016293,
0.007455247920006514,
0... |
Anubhav23/model_name | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Cartpolev2
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_rewar... | [
-0.03051091358065605,
0.01623404026031494,
0.0037324854638427496,
0.010680344887077808,
0.04453345388174057,
-0.017600949853658676,
-0.024408316239714622,
-0.019182519987225533,
-0.02966705523431301,
0.08315115422010422,
0.018153240904211998,
-0.007714758161455393,
0.011068401858210564,
0.... |
Anupam/QuestionClassifier | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... | [
-0.03752153366804123,
-0.002777367364615202,
-0.005121125839650631,
0.025110946968197823,
0.04550165310502052,
-0.02134954370558262,
-0.005261690355837345,
-0.027728311717510223,
-0.0334872268140316,
0.06642544269561768,
0.03251560777425766,
-0.02363228052854538,
0.022600147873163223,
0.00... |
Apoorva/k2t-test | [
"pytorch",
"t5",
"text2text-generation",
"en",
"transformers",
"keytotext",
"k2t",
"Keywords to Sentences",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_s... | 7 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-all
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment.... | [
-0.041427481919527054,
-0.00998977292329073,
0.004018416162580252,
0.034561242908239365,
0.023237839341163635,
0.022495971992611885,
-0.015858393162488937,
-0.0042663803324103355,
-0.02777656354010105,
0.0474892258644104,
0.0265860203653574,
-0.0492582768201828,
0.021186616271734238,
0.035... |
Appolo/TestModel | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: speller-t5-900
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# speller-t5-900
This mo... | [
-0.012978644110262394,
-0.011201087385416031,
-0.00519738020375371,
0.042115867137908936,
0.045090414583683014,
0.010592110455036163,
-0.022360272705554962,
-0.019755976274609566,
-0.0633886307477951,
0.04476403817534447,
0.015804005786776543,
-0.034451309591531754,
-0.00797079224139452,
0... |
ArBert/albert-base-v2-finetuned-ner-agglo-twitter | [
"pytorch",
"tensorboard",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"AlbertForTokenClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 27 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: PixelCopter1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
metrics:... | [
-0.04284653812646866,
0.013380573131144047,
0.01462524849921465,
0.020583152770996094,
0.04900495335459709,
-0.012847351841628551,
-0.020623713731765747,
-0.026865079998970032,
-0.016759714111685753,
0.06570304185152054,
0.03638099506497383,
-0.006967758294194937,
0.007904509082436562,
-0.... |
ArBert/albert-base-v2-finetuned-ner-kmeans | [
"pytorch",
"tensorboard",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"AlbertForTokenClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 8 | null | ---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: huynhdoo/distilcamembert-base-finetuned-jva-missions-report
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove th... | [
-0.058438852429389954,
-0.018299825489521027,
-0.005121632944792509,
0.012822103686630726,
0.03986222296953201,
0.014048939570784569,
-0.003120644949376583,
-0.009156031534075737,
-0.02893429808318615,
0.04636875167489052,
0.026408009231090546,
-0.03255889192223549,
0.0024311495944857597,
... |
ArBert/albert-base-v2-finetuned-ner | [
"pytorch",
"tensorboard",
"albert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"AlbertForTokenClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 19 | null | ---
language:
- hi
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- logistics
model-index:
- name: Whisper base Hi - BeaW
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then rem... | [
-0.038621287792921066,
0.006664973217993975,
-0.014675823040306568,
0.04968990013003349,
0.04594479128718376,
0.02706817165017128,
0.0068453289568424225,
0.01069249864667654,
-0.0095591451972723,
0.04603996127843857,
0.04744580760598183,
-0.019433289766311646,
-0.0027673442382365465,
0.036... |
ArBert/bert-base-uncased-finetuned-ner-agglo | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language:
- en
datasets:
- English
tags:
- text generation
- pytorch
- causal-lm
- Writer-data
- gpt
- NeMo
pipeline_tag: text-generation
library_name: transformers
license: apache-2.0
---
# Palmyra Base 5B
<style>
img {
display: inline;
}
</style>
|[![Model architecture](https://img.shields.io/badge/Model%20... | [
-0.02276800572872162,
-0.010855469852685928,
-0.03179290145635605,
0.06901557743549347,
0.04666101187467575,
0.027618804946541786,
0.0037298016250133514,
-0.006242162548005581,
-0.025117112323641777,
0.0585319809615612,
0.02194209210574627,
-0.03857095167040825,
-0.025477638468146324,
0.02... |
ArBert/bert-base-uncased-finetuned-ner-kmeans-twitter | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language:
- en
datasets:
- English
tags:
- text generation
- pytorch
- causal-lm
- Writer-data
- NeMo
pipeline_tag: text-generation
library_name: transformers
license: apache-2.0
---
license: cc-by-4.0
# Palmyra Small 128M
<style>
img {
display: inline;
}
</style>
|[![Model architecture](https://img.shields.i... | [
-0.009942888282239437,
-0.0005331556312739849,
-0.021069122478365898,
0.06791088730096817,
0.04599958285689354,
0.01629767380654812,
0.0035993901547044516,
-0.011446642689406872,
-0.025474943220615387,
0.07407642155885696,
0.015242202207446098,
-0.031194590032100677,
-0.033544156700372696,
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.