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 |
|---|---|---|---|---|---|---|---|
Dawit/DialogGPT-small-ironman | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
tags:
- mteb
model-index:
- name: all-mpnet-base-v2-negation
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
me... | [
-0.028882669284939766,
-0.006081268656998873,
-0.02470005303621292,
0.036451201885938644,
0.042440976947546005,
0.03818970173597336,
-0.02314832992851734,
-0.010403276421129704,
-0.05595299229025841,
0.04324811324477196,
0.03566019609570503,
0.004173649474978447,
0.02075083926320076,
0.045... |
Daymarebait/Discord_BOT_RICK | [
"conversational"
] | conversational | {
"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... | 3 | null | ---
library_name: ml-agents
tags:
- SnowballTarget
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SnowballTarget
---
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Tech... | [
-0.02874402515590191,
-0.0043599558994174,
-0.018111051991581917,
0.05237302929162979,
0.036014486104249954,
0.025499317795038223,
-0.0029192264191806316,
-0.03497467562556267,
-0.025094663724303246,
0.04614902660250664,
0.025857161730527878,
-0.008787826634943485,
0.019061796367168427,
0.... |
Dazai/Ko | [] | 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
language:
- pl
tags:
- llama
- alpaca
- lora
- self-instruct
---
This repo contains a low-rank adapter for LLaMA-7B trained on generated (not translated!) 55125 [instructions](https://huggingface.co/datasets/chrisociepa/raw-self-generated-instructions-pl) in Polish.
The training took almost 16 hours ... | [
-0.02890850231051445,
0.0010311544174328446,
-0.009337600320577621,
0.04537922143936157,
0.045622799545526505,
0.011010640300810337,
0.003363987198099494,
0.0012999842874705791,
-0.0315919890999794,
0.07153885811567307,
0.03508516773581505,
-0.051174674183130264,
-0.02423553541302681,
0.02... |
Dazai/Ok | [] | 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 | คุณกำลังสงสัยอยู่ใช่หรือไม่ว่าสล็อตคืออะไร ? หากคุณลองค้นหาข้อมูลตามอินเตอร์เน็ตทั่วไปจะพบว่า PG SLOT คือเครื่องเล่นพนันชนิดหนึ่งที่มีลักษณะเป็นตู้สี่เหลี่ยม มีคันโยกคล้ายกับเกียร์รถยนต์เพื่อใช้ในการเริ่มต้นเล่นเกมและที่ตู้สี่เหลี่ยมนี้จะมีหน้าจอคล้ายกับโทรทัศน์จอแก้วเป็นหน้าจอในการแสดงผลของเกม ซึ่งในสมัยก่อนนั้นสัญลัก... | [
-0.024604560807347298,
0.008900359272956848,
0.008758317679166794,
0.03364790230989456,
0.028098804876208305,
0.011569218710064888,
0.009935619309544563,
0.001810005633160472,
-0.014888261444866657,
0.039852339774370193,
0.03504200279712677,
0.000013592488357971888,
0.03417038917541504,
0.... |
DecafNosebleed/DialoGPT-small-ScaraBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 15 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: HASAN55/bert-finetuned-for-uncased
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. -->
#... | [
-0.01862381026148796,
-0.0026379013434052467,
-0.016414940357208252,
0.034323688596487045,
0.02738230861723423,
0.01867799647152424,
-0.023000657558441162,
-0.029172739014029503,
-0.04183361679315567,
0.05011583864688873,
0.01116834208369255,
-0.03242640942335129,
0.03827424347400665,
0.04... |
DecafNosebleed/scarabot-model | [
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | 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
... | [
-0.03734922036528587,
-0.017791947349905968,
-0.015632696449756622,
0.0371423177421093,
0.04868689551949501,
-0.004641760140657425,
-0.015163675881922245,
-0.02620556950569153,
-0.030707649886608124,
0.0543886162340641,
0.020071273669600487,
-0.03259213641285896,
0.017292561009526253,
0.01... |
Declan/Breitbart_model_v4 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: spam-classifier
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. -->
#... | [
-0.00972922332584858,
0.0029619259294122458,
-0.014493553899228573,
0.03638404235243797,
0.0589582733809948,
0.024849098175764084,
-0.009195405058562756,
-0.0052908677607774734,
-0.019916998222470284,
0.05709594488143921,
0.03413299098610878,
-0.006454709451645613,
0.0015122402692213655,
0... |
Declan/Breitbart_model_v5 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: TestZee/mt5-small-finetuned-mt5-Large-English-Test
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... | [
-0.03717365860939026,
-0.01626681722700596,
0.01786390133202076,
0.020496830344200134,
0.03373495116829872,
0.008335262537002563,
-0.030428074300289154,
-0.011123867705464363,
-0.02952810749411583,
0.0618913359940052,
0.02010314166545868,
-0.032228950411081314,
0.022123223170638084,
0.0357... |
Declan/Breitbart_model_v7 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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... | 5 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep5_lr2
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 remo... | [
-0.005145959556102753,
-0.011602997779846191,
-0.010492313653230667,
0.046054333448410034,
0.011845930479466915,
0.02015739493072033,
-0.02431626059114933,
-0.026620585471391678,
-0.038632456213235855,
0.05980386957526207,
0.006155082024633884,
-0.05193042755126953,
0.01593034341931343,
0.... |
Declan/Breitbart_model_v8 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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 | null | ---
tags:
- bert
- adapter-transformers
- adapterhub:reginaboateng/cleaned_pubmedqa
datasets:
- pubmedqa
---
# Adapter `reginaboateng/pubmedqa-adapter` for allenai/scibert_scivocab_uncased
An [adapter](https://adapterhub.ml) for the `allenai/scibert_scivocab_uncased` model that was trained on the [reginaboateng/clean... | [
-0.03659086301922798,
-0.018951954320073128,
-0.015788888558745384,
0.060771115124225616,
0.025398168712854385,
0.02541937865316868,
-0.034620825201272964,
-0.019834162667393684,
-0.06197275221347809,
0.055184151977300644,
-0.009100872091948986,
0.00036136319977231324,
0.009592567570507526,
... |
Declan/Breitbart_modelv7 | [] | 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
base_model: /root/stable-diffusion-v1-5
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- lora
inference: true
---
# LoRA text2image fine-tuning - raven316/pokemon-lora
These are LoRA adaption weights for /root/stable-diffusion-v1-5. The weights... | [
-0.027619633823633194,
-0.013955876231193542,
-0.015858231112360954,
0.0164085291326046,
0.043072812259197235,
-0.011008912697434425,
0.008793427608907223,
-0.016980547457933426,
-0.008391845971345901,
0.06076468899846077,
0.02276354655623436,
-0.030304118990898132,
0.016074227169156075,
0... |
Declan/CNN_model_v3 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-samsum-ElectrifAi_v12
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 comm... | [
-0.03138016164302826,
-0.003499598940834403,
-0.011059324257075787,
0.042446255683898926,
0.0369425006210804,
0.015240080654621124,
-0.01636105589568615,
-0.026139035820961,
-0.06077186390757561,
0.055034104734659195,
0.041200876235961914,
-0.006777987815439701,
0.01753827929496765,
0.0471... |
Declan/CNN_model_v4 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: ec-biogpt-noised-pubmed-v2
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. -->
# ec-biogpt-noise... | [
-0.022208455950021744,
-0.004573948215693235,
-0.0009412409854121506,
0.009138434194028378,
0.028207607567310333,
0.01925966516137123,
0.003001599106937647,
-0.005651720799505711,
-0.028862537816166878,
0.04471667855978012,
0.01643132045865059,
-0.026892445981502533,
0.014015769585967064,
... |
Declan/CNN_model_v8 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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 | null |
---
license: creativeml-openrail-m
base_model: runwayml/stable-diffusion-v1-5
instance_prompt: photo of a sks plushy
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- svdiff
inference: true
---
# SVDiff-pytorch - mshing/svdiff_kumamon_example
These are SVDiff weights for runwayml/sta... | [
-0.03464286029338837,
-0.011695855297148228,
-0.01659293845295906,
0.020701397210359573,
0.026899045333266258,
0.004567343275994062,
-0.0013828239170834422,
0.008100951090455055,
-0.013127114623785019,
0.061381276696920395,
0.023325372487306595,
-0.00657255481928587,
-0.003181337844580412,
... |
Declan/ChicagoTribune_model_v4 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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... | 7 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: my_awesome_billsum_model
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: billsum
type: billsum
config: default
... | [
-0.007746822666376829,
-0.007551489397883415,
-0.004060653038322926,
0.021539703011512756,
0.015489144250750542,
0.016549844294786453,
-0.017170030623674393,
-0.023287838324904442,
-0.04065752774477005,
0.045883938670158386,
0.038087695837020874,
-0.009120423346757889,
-0.017311153933405876,... |
Declan/ChicagoTribune_model_v6 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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... | 5 | 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
... | [
-0.03978508338332176,
-0.01676926761865616,
-0.015304683707654476,
0.036482758820056915,
0.048391349613666534,
-0.004881933331489563,
-0.013249414972960949,
-0.024651264771819115,
-0.030913105234503746,
0.05454813688993454,
0.022156618535518646,
-0.03231290355324745,
0.018666330724954605,
... |
Declan/ChicagoTribune_model_v7 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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... | 7 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: HF_DRL_U4_pixelcopter_reinforcepg_v2
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelco... | [
-0.03690747916698456,
0.013344773091375828,
0.011524350382387638,
0.02004505693912506,
0.05233323574066162,
-0.011883603408932686,
-0.017565960064530373,
-0.023347033187747,
-0.0145238246768713,
0.06522460281848907,
0.03538069874048233,
-0.0032019726932048798,
0.007168849930167198,
-0.0031... |
Declan/ChicagoTribune_model_v8 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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... | 7 | null | ---
license: apache-2.0
---
# Introduction
This repo contains torchscript model of `stt_en_conformer_ctc_medium` from NeMo.
See https://registry.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_en_conformer_ctc_medium
The following code is used to obtain `model.onnx` and `tokens.txt`:
```python3
m = nemo_asr.model... | [
-0.039615556597709656,
-0.008919238112866879,
-0.005177337676286697,
0.016255522146821022,
0.050715938210487366,
0.02022496797144413,
-0.020689884200692177,
-0.004572013858705759,
-0.05036067217588425,
0.04334021732211113,
0.05391133949160576,
0.002432276029139757,
0.023630637675523758,
0.... |
Declan/FoxNews_model_v1 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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 | null | ---
tags:
- adapter-transformers
- bert
- adapterhub:biomedical/pubmedqa
datasets:
- pubmedqa
---
# Adapter `reginaboateng/pubmedqa_adapter` for allenai/scibert_scivocab_uncased
An [adapter](https://adapterhub.ml) for the `allenai/scibert_scivocab_uncased` model that was trained on the [biomedical/pubmedqa](https://a... | [
-0.043087199330329895,
-0.022727221250534058,
-0.012523075565695763,
0.05705798417329788,
0.028741633519530296,
0.02546384185552597,
-0.029381556436419487,
-0.018547281622886658,
-0.054317910224199295,
0.05224031209945679,
-0.0029959273524582386,
-0.003384990617632866,
0.006616588216274977,
... |
Declan/FoxNews_model_v4 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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... | 7 | null | ---
license: apache-2.0
---
# Introduction
This repo contains torchscript model of `stt_en_conformer_ctc_large` from NeMo.
See https://registry.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_en_conformer_ctc_large
The following code is used to obtain `model.onnx` and `tokens.txt`:
```python3
m = nemo_asr.models.... | [
-0.040868498384952545,
-0.011522087268531322,
0.0037049308884888887,
0.017873598262667656,
0.05359027162194252,
0.008477496914565563,
-0.022706586867570877,
-0.01910257525742054,
-0.039787739515304565,
0.040827248245477676,
0.06011001765727997,
0.008345833979547024,
0.016834229230880737,
0... |
Declan/FoxNews_model_v5 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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... | 7 | null | # Lora模型使用介绍
## Celestine Lucullus
2023/2/25 update
Prune tags to make the description more accurate. Adjust rank to 32 to balance file size and quality.
Introduction
A LORA model of Celestine Lucullus from Kuroinu. The 784mb VAEs (NAI, Orangemix, Anything, Counterfeit) are recommended. 0.6~0.8 weights are good. It‘s ... | [
0.004559561610221863,
-0.021525461226701736,
-0.007882017642259598,
0.04308197647333145,
0.07043987512588501,
-0.011553785763680935,
-0.013991818763315678,
-0.007184737361967564,
-0.002220829715952277,
0.052007488906383514,
0.04477666690945625,
-0.0212821327149868,
0.004318655002862215,
0.... |
Declan/HuffPost_model_v2 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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 | null | ---
license: mit
tags:
- translation
- generated_from_trainer
metrics:
- bleu
model-index:
- name: m2m100_418M-english-somali-v2.0
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 t... | [
-0.026389572769403458,
-0.003111282829195261,
-0.0038784302305430174,
0.04857921600341797,
0.0227179154753685,
0.013893598690629005,
-0.014792154543101788,
0.0029592057690024376,
-0.05008606240153313,
0.06415574997663498,
0.02612326666712761,
-0.03493145480751991,
0.027324555441737175,
0.0... |
Declan/HuffPost_model_v6 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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... | 9 | null | ---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/model-cards
{}
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base tem... | [
-0.03477105498313904,
-0.01037435233592987,
0.00011377478222129866,
0.015253852121531963,
0.02282647229731083,
0.044932618737220764,
-0.020595461130142212,
-0.026462821289896965,
-0.028890972957015038,
0.04969323053956032,
0.022915950044989586,
-0.006789288017898798,
0.03135347738862038,
0... |
Declan/HuffPost_model_v8 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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... | 7 | null | ---
tags:
- autotrain
- summarization
language:
- unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- PavelDanek/autotrain-data-s2gsummarize
co2_eq_emissions:
emissions: 15.760105221870123
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 47615116641
- CO2 Emissions (in grams): 15.7601... | [
-0.01855519227683544,
-0.019111353904008865,
0.004868983756750822,
0.028486991301178932,
0.03919684886932373,
0.014773703180253506,
-0.03615139424800873,
-0.01721022091805935,
-0.050334639847278595,
0.08144678175449371,
0.025096451863646507,
0.028222741559147835,
0.013912800699472427,
0.03... |
Declan/NPR_model_v1 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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 | 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... | [
-0.021968163549900055,
-0.005475083831697702,
0.01037929579615593,
0.0396992564201355,
0.03235756978392601,
0.015414402820169926,
-0.028452729806303978,
-0.016240393742918968,
-0.014965358190238476,
0.061603445559740067,
0.006659382022917271,
0.0006855895044282079,
0.010951911099255085,
0.... |
Declan/NPR_model_v3 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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... | 9 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: HFRLu4_CartPole
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_... | [
-0.030653567984700203,
0.013372628949582577,
-0.0028349063359200954,
0.012458670884370804,
0.04064058139920235,
-0.016366638243198395,
-0.02384154312312603,
-0.022128520533442497,
-0.030039753764867783,
0.07923642545938492,
0.015063054859638214,
-0.008834907785058022,
0.012670195661485195,
... |
Declan/NPR_model_v5 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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... | 7 | null | ---
library_name: ml-agents
tags:
- Pyramids
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
... | [
-0.05208984389901161,
0.0023469917941838503,
-0.005036073736846447,
0.050746988505125046,
0.02466176077723503,
0.030617916956543922,
-0.011871248483657837,
-0.02402898482978344,
-0.00040282862028107047,
0.0501721166074276,
0.02530062571167946,
-0.013805573806166649,
0.007268661633133888,
0... |
Declan/WallStreetJournal_model_v1 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | 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 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: vit-base-patch16-224-finetuned-flower
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 r... | [
-0.028624797239899635,
-0.01777588576078415,
0.011208129115402699,
0.022029966115951538,
0.02487098053097725,
-0.003307791892439127,
-0.012061079032719135,
-0.0042292275466024876,
-0.005965603515505791,
0.040048085153102875,
0.040736205875873566,
0.001478572841733694,
0.026534348726272583,
... |
DeskDown/MarianMixFT_en-ms | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"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 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: bert-fine-tuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: cola
split: validation... | [
-0.013762266375124454,
0.006481001619249582,
-0.008398260921239853,
0.037535954266786575,
0.06089093163609505,
0.018165793269872665,
-0.03308216109871864,
-0.02214163914322853,
-0.040620751678943634,
0.05355878919363022,
0.021011091768741608,
-0.005776858422905207,
0.026657553389668465,
0.... |
DeskDown/MarianMixFT_en-th | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"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 | null | ---
license: creativeml-openrail-m
---
created by https://civitai.com/user/AreThoseLevel4Plates
all credits reserved to the creator
uploaded only for personal use in colab | [
-0.0377529039978981,
-0.0036640805192291737,
-0.027673596516251564,
-0.0030059602577239275,
0.05200958251953125,
0.028830846771597862,
-0.0005272143171168864,
-0.0006010226206853986,
-0.041499681770801544,
0.036114033311605453,
0.04851074516773224,
0.021274607628583908,
0.0218599122017622,
... |
DeskDown/MarianMix_en-ja-10 | [
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"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 | 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... | [
-0.017882267013192177,
-0.017891855910420418,
-0.007616735994815826,
0.030247099697589874,
0.050898127257823944,
-0.016720451414585114,
-0.011871492490172386,
-0.009876490570604801,
-0.058948975056409836,
0.05417945608496666,
-0.0036142836324870586,
-0.008653889410197735,
0.02448650822043419... |
DeskDown/MarianMix_en-zh-10 | [
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"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 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
- relation-extraction
metrics:
- rouge
model-index:
- name: t5-base-DreamBank-Generation-Act-Char
results: []
language:
- en
inference:
parameters:
max_length: 128
widget:
- text: >-
I was skating on the outdoor ice pond that used to be across the stree... | [
-0.028296397998929024,
-0.02004498988389969,
-0.013319417834281921,
0.008372697047889233,
0.037568069994449615,
0.014424869790673256,
-0.030775392428040504,
0.008102740161120892,
-0.053256623446941376,
0.023822862654924393,
0.04406483843922615,
-0.019498033449053764,
-0.020533574745059013,
... |
Despin89/test | [] | 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
---
### Drachenlord-x-Protogen-Dreambooth
Sample prompt:
modelshoot style, (extremely detailed CG unity 8k wallpaper), ((((full body portrait)))) photo of a (((very morbidly obese, fat lumps, wounds, diabetes))) (((drachenlord))), portrait a... | [
0.009568306617438793,
-0.02931317873299122,
0.005459474865347147,
0.034039080142974854,
0.06330173462629318,
0.0351116918027401,
-0.002130780601873994,
-0.03363390266895294,
0.006712940521538258,
0.037773497402668,
0.05081242322921753,
-0.00892543513327837,
0.003042705124244094,
0.06517338... |
Devmapall/paraphrase-quora | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"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... | 3 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-Taxi-v3-baseline
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.42... | [
-0.0191874410957098,
-0.01655743457376957,
-0.008872670121490955,
0.02485590986907482,
0.04645417630672455,
-0.0013765833573415875,
-0.017416086047887802,
0.006668915506452322,
-0.03586377203464508,
0.05183030292391777,
0.014917892403900623,
-0.008980859071016312,
0.011178601533174515,
0.0... |
DevsIA/Devs_IA | [] | 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 | 2023-04-07T15:43:39Z | ---
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... | [
-0.05004018172621727,
-0.016386041417717934,
-0.008802029304206371,
0.036186378449201584,
0.040622033178806305,
0.0032270336523652077,
-0.021389879286289215,
-0.010173819959163666,
-0.038117360323667526,
0.057175084948539734,
0.024408582597970963,
-0.0029793167486786842,
0.031521160155534744... |
DheerajPranav/Dialo-GPT-Rick-bot | [] | 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:
- 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
... | [
-0.04134152829647064,
0.016154596582055092,
0.014397243037819862,
0.016960954293608665,
0.04861651733517647,
-0.012946301139891148,
-0.020393069833517075,
-0.023326167836785316,
-0.01661393605172634,
0.06838896125555038,
0.036128949373960495,
-0.00725666806101799,
0.012477689422667027,
-0.... |
Dilmk2/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 13 | null | ---
language:
- ru
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Russian
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name... | [
-0.036178551614284515,
-0.01439322717487812,
-0.010875323787331581,
0.04528018832206726,
0.05451595038175583,
0.02167552150785923,
-0.008565685711801052,
-0.011029318906366825,
-0.034837692975997925,
0.0744805708527565,
0.04266795143485069,
-0.03520785644650459,
0.004153421148657799,
0.028... |
DingleyMaillotUrgell/homer-bot | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: taxiv3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.50 +/- 2.76
... | [
-0.018998252227902412,
-0.015305769629776478,
-0.004503471311181784,
0.023816214874386787,
0.044882018119096756,
-0.0020596743561327457,
-0.019989948719739914,
0.006714127492159605,
-0.03587395325303078,
0.05388795584440231,
0.017507076263427734,
-0.007492951583117247,
0.01331180240958929,
... |
DongHai/DialoGPT-small-rick | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | 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... | [
-0.04004170000553131,
0.016245169565081596,
0.014509264379739761,
0.017345471307635307,
0.04867767542600632,
-0.013779613189399242,
-0.020160609856247902,
-0.023495523259043694,
-0.017506344243884087,
0.06779745221138,
0.03538889065384865,
-0.007815375924110413,
0.011196673847734928,
-0.00... |
Waynehillsdev/Waynehills_summary_tensorflow | [
"tf",
"t5",
"text2text-generation",
"transformers",
"generated_from_keras_callback",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 5 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: cartpole
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_reward
... | [
-0.03340867906808853,
0.017721671611070633,
-0.0006116053555160761,
0.009832113981246948,
0.046157315373420715,
-0.019046952947974205,
-0.021131202578544617,
-0.02123243920505047,
-0.03375647962093353,
0.08470679074525833,
0.020631007850170135,
-0.011456693522632122,
0.01258950587362051,
0... |
DoyyingFace/bert-asian-hate-tweets-asian-unclean-freeze-12 | [
"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... | 29 | 2023-04-07T16:58:23Z | ---
language:
- hi
license: apache-2.0
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-common_voice-hi-demo
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
datase... | [
-0.03466762602329254,
-0.00610203156247735,
-0.02090907096862793,
0.03213346004486084,
0.05347692593932152,
0.03391663357615471,
-0.01123298890888691,
-0.017763232812285423,
-0.019847624003887177,
0.056530240923166275,
0.028047852218151093,
-0.025181515142321587,
0.012152859941124916,
0.02... |
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 | 2023-04-07T17:41:44Z | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: pixelcopter
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
metrics:
... | [
-0.04228762909770012,
0.013796818442642689,
0.014590886421501637,
0.01944648288190365,
0.04964829981327057,
-0.013262320309877396,
-0.019030964002013206,
-0.02898205816745758,
-0.01643919199705124,
0.06562907993793488,
0.03729492798447609,
-0.007414415944367647,
0.008556883782148361,
-0.00... |
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 | 2023-04-07T17:46:03Z | ---
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
... | [
-0.04188288003206253,
-0.018457286059856415,
-0.012884882278740406,
0.03502841666340828,
0.04467425495386124,
-0.005748976022005081,
-0.011760318651795387,
-0.022389547899365425,
-0.03178549185395241,
0.047689229249954224,
0.024389956146478653,
-0.03208908438682556,
0.014552759006619453,
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 | 2023-04-07T17:47:42Z | ---
library_name: ml-agents
tags:
- SnowballTarget
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SnowballTarget
---
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Tech... | [
-0.029720233753323555,
-0.0056360443122684956,
-0.016600362956523895,
0.05099621042609215,
0.03637174144387245,
0.02677598036825657,
-0.002534541767090559,
-0.034081634134054184,
-0.024695517495274544,
0.047533199191093445,
0.025644103065133095,
-0.008478023111820221,
0.018820812925696373,
... |
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 | 2023-04-07T17:47:47Z | ---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- billster45/autotrain-data-news_headlines
co2_eq_emissions:
emissions: 0.47291454067852207
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 47662116693
- CO2 Emission... | [
-0.016661563888192177,
-0.022587787359952927,
-0.01002577319741249,
0.035714779049158096,
0.03995372727513313,
0.0389290526509285,
-0.03054823912680149,
-0.0189753957092762,
-0.04614465311169624,
0.07884766906499863,
0.0217598844319582,
0.020558202639222145,
-0.00009693978063296527,
0.0311... |
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 | 2023-04-07T17:55:00Z | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-base-timit-mseva
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. -->
# wav2vec2-... | [
-0.03329882770776749,
-0.015399232506752014,
-0.022906571626663208,
0.012729835696518421,
0.03951499983668327,
0.035717595368623734,
0.00939998310059309,
0.00503140315413475,
-0.03294316306710243,
0.04965454339981079,
0.03772873803973198,
-0.0116262286901474,
0.011043606325984001,
0.034977... |
bert-base-german-dbmdz-cased | [
"pytorch",
"jax",
"bert",
"fill-mask",
"de",
"transformers",
"license:mit",
"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... | 1,814 | 2023-04-07T17:58:58Z | ---
tags:
- FrozenLake-v1-4x4
- 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
type: FrozenLake-v1-4x4
metrics:... | [
-0.011721031740307808,
-0.015278352424502373,
-0.003129095770418644,
0.030731989070773125,
0.050463758409023285,
-0.01412035059183836,
-0.013181601651012897,
-0.008123347535729408,
-0.05732106417417526,
0.05594724789261818,
0.001691925572231412,
-0.006440441124141216,
0.026986362412571907,
... |
bert-large-cased-whole-word-masking-finetuned-squad | [
"pytorch",
"tf",
"jax",
"rust",
"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... | 8,214 | 2023-04-07T18:09:23Z | ---
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
... | [
-0.023158065974712372,
-0.007685904856771231,
-0.007209536619484425,
0.02725333906710148,
0.0480576753616333,
-0.02137034572660923,
-0.0056778001599013805,
-0.019131137058138847,
-0.03686051815748215,
0.07532867789268494,
0.02512715943157673,
-0.027415834367275238,
0.0086018992587924,
0.01... |
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 | 2023-04-07T19:34:59Z | ---
license: cc-by-4.0
tags:
- generated_from_trainer
datasets:
- wmt16
metrics:
- bleu
model-index:
- name: opus-mt-en-de-finetuned-en-to-de
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: wmt16
type: wmt16
config: de-en
... | [
-0.013542259112000465,
-0.00711418641731143,
0.0012007562909275293,
0.03894832357764244,
0.03230489045381546,
0.008849548175930977,
-0.009801509790122509,
-0.020878048613667488,
-0.023388441652059555,
0.05664237588644028,
0.01429039891809225,
-0.0219682939350605,
-0.016931109130382538,
0.0... |
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 | 2023-04-07T18:23:12Z | ---
license: mit
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: test-dialogue-summarization
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
config: samsum
spli... | [
-0.016326483339071274,
-0.0009329026215709746,
-0.016753382980823517,
0.05216052383184433,
0.03944488987326622,
0.027342770248651505,
-0.01600690558552742,
-0.033616773784160614,
-0.04817409813404083,
0.06469234079122543,
0.03538822382688522,
-0.03176691383123398,
0.015248920768499374,
0.0... |
distilbert-base-uncased-finetuned-sst-2-english | [
"pytorch",
"tf",
"rust",
"safetensors",
"distilbert",
"text-classification",
"en",
"dataset:sst2",
"dataset:glue",
"arxiv:1910.01108",
"doi:10.57967/hf/0181",
"transformers",
"license:apache-2.0",
"model-index",
"has_space"
] | 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,
... | 3,060,704 | 2023-04-07T18:30:45Z | ---
license: other
tags:
- image-segmentation
- vision
- generated_from_trainer
model-index:
- name: segformer-finetuned-lane-10k-steps
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... | [
-0.01840655691921711,
-0.003736925544217229,
-0.005113385152071714,
0.01123964972794056,
0.01972927153110504,
0.005513387266546488,
-0.012904679402709007,
0.011291863396763802,
-0.058412909507751465,
0.0546804741024971,
0.04065917432308197,
-0.004863736219704151,
-0.0012207935797050595,
0.... |
AdapterHub/bert-base-uncased-pf-squad_v2 | [
"bert",
"en",
"dataset:squad_v2",
"arxiv:2104.08247",
"adapter-transformers",
"question-answering",
"adapterhub:qa/squad2"
] | question-answering | {
"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... | 10 | null |
# vicuna-13b
This README provides a step-by-step guide to set up and run the FastChat application with the required dependencies and model.
## Prerequisites
Before you proceed, ensure that you have `git` installed on your system.
## Installation
Follow the steps below to install the required packages and set up t... | [
-0.016294755041599274,
-0.015547866933047771,
-0.00568418251350522,
-0.005689764861017466,
0.04758627712726593,
0.0074799759313464165,
-0.0027421859558671713,
0.0048373909667134285,
-0.019606400281190872,
0.04383218288421631,
0.027843302115797997,
0.02507750503718853,
0.05052535980939865,
... |
AdapterHub/roberta-base-pf-cola | [
"roberta",
"en",
"arxiv:2104.08247",
"adapter-transformers",
"text-classification",
"adapterhub:lingaccept/cola"
] | 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_... | 0 | null | ---
tags:
- generated_from_trainer
datasets:
- aeslc
metrics:
- rouge
model-index:
- name: pegasus-large-finetuned-aeslc
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: aeslc
type: aeslc
config: default
split: validation... | [
-0.021042145788669586,
-0.005783989559859037,
0.0021430819761008024,
0.032817527651786804,
0.057099007070064545,
-0.0011133900843560696,
-0.017753079533576965,
-0.034121785312891006,
-0.018175315111875534,
0.054413046687841415,
0.003580409102141857,
-0.014532813802361488,
-0.0061725680716335... |
Aleksandar/distilbert-srb-ner-setimes | [
"pytorch",
"distilbert",
"token-classification",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"DistilBertForTokenClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 3 | 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
... | [
-0.037457678467035294,
-0.0026413830928504467,
-0.0052527254447340965,
0.025413986295461655,
0.04567775875329971,
-0.02147757261991501,
-0.0054621570743620396,
-0.028147529810667038,
-0.03310275077819824,
0.06654872745275497,
0.03238367289304733,
-0.023288514465093613,
0.022870663553476334,
... |
Aleksandar/electra-srb-ner | [
"pytorch",
"safetensors",
"electra",
"token-classification",
"dataset:wikiann",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"ElectraForTokenClassification"
],
"model_type": "electra",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_... | 15 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### RFIA2 Dreambooth model trained by HuggM3 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 [fast-Co... | [
-0.031356051564216614,
-0.020388415083289146,
-0.029663585126399994,
0.027797376736998558,
0.02716679684817791,
0.014887388795614243,
0.0022513701114803553,
-0.000927689834497869,
-0.014982731081545353,
0.033570609986782074,
0.03629302233457565,
0.01098227221518755,
-0.02475915290415287,
0... |
Alexander-Learn/bert-finetuned-squad-accelerate | [] | 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: ml-agents
tags:
- Pyramids
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
... | [
-0.05191407725214958,
0.0018372953636571765,
-0.004423616454005241,
0.050312358886003494,
0.026503410190343857,
0.03075782209634781,
-0.0112345851957798,
-0.022464781999588013,
-0.003144554328173399,
0.05060327425599098,
0.025902770459651947,
-0.012884645722806454,
0.007867018692195415,
0.... |
Andrija/M-bert-NER | [
"pytorch",
"bert",
"token-classification",
"hr",
"sr",
"multilingual",
"dataset:hr500k",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"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... | 8 | 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... | [
-0.04991859197616577,
-0.015945948660373688,
-0.00884153414517641,
0.03636012226343155,
0.04101625457406044,
0.00307828257791698,
-0.021458428353071213,
-0.010494058951735497,
-0.03780028969049454,
0.057075563818216324,
0.024692445993423462,
-0.00306907226331532,
0.03162853792309761,
0.002... |
AnonymousSub/SR_EManuals-BERT | [
"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... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: t5-small_finetuned_billsum_model_bs8_lr5e-05
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: billsum
type: billsum
... | [
0.0003418138949200511,
0.0057349191047251225,
-0.00011543682921910658,
0.017666669562458992,
0.021231722086668015,
0.015987956896424294,
-0.023620013147592545,
-0.014874052256345749,
-0.04706535488367081,
0.03817189484834671,
0.03453417867422104,
-0.02576603554189205,
-0.00002045643122983165... |
AnonymousSub/SR_EManuals-RoBERTa | [
"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... | 1 | 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
... | [
-0.03738902509212494,
-0.002441592514514923,
-0.004952242132276297,
0.025158870965242386,
0.04550046846270561,
-0.02181093767285347,
-0.0054804435931146145,
-0.02812812104821205,
-0.03298848494887352,
0.0666903555393219,
0.03269176185131073,
-0.023436637595295906,
0.022411998361349106,
0.0... |
AnonymousSub/cline-s10-AR | [
"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,
"... | 31 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforece-cartpole_policyV1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
... | [
-0.02484583854675293,
0.01899748481810093,
0.0018095036502927542,
0.011015561409294605,
0.04546782746911049,
-0.015517228282988071,
-0.019478462636470795,
-0.020763656124472618,
-0.02992517501115799,
0.07875583320856094,
0.016717778518795967,
-0.01524896640330553,
0.015579013153910637,
0.0... |
AnonymousSub/rule_based_bert_hier_diff_equal_wts_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 | 2021-11-04T21:11:11Z | ---
language: en
tags:
- azbert
- pretraining
- fill-mask
widget:
- text: "$f$ $($ $x$ [MASK] $y$ $)$"
example_title: "mathy"
- text: "$x$ [MASK] $x$ $equal$ $2$ $x$"
example_title: "mathy"
- text: "Proof by [MASK] that $n$ $fact$ $gt$ $3$ $n$ for $n$ $gt$ $6$"
example_title: "mathy"
- text: "Proof by induction t... | [
-0.028382282704114914,
-0.01592629961669445,
0.016943592578172684,
0.050396669656038284,
0.022899547591805458,
0.01700987108051777,
-0.030220165848731995,
-0.01376965083181858,
-0.011364035308361053,
0.06336038559675217,
0.004339843522757292,
0.008322021923959255,
0.02630140446126461,
0.04... |
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: apache-2.0
tags:
- generated_from_trainer
datasets:
- esnli
metrics:
- accuracy
- f1
- rouge
- bleu
model-index:
- name: google-flan-t5-small-e-snli-generation-label_and_explanation-selected-b48
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dat... | [
-0.0065686702728271484,
0.008435097523033619,
-0.0009135175496339798,
0.03605549409985542,
0.03689209744334221,
-0.001660753390751779,
-0.014827556908130646,
-0.016716375946998596,
-0.03032277710735798,
0.04769199341535568,
0.006004130933433771,
-0.029809780418872833,
-0.007921028882265091,
... |
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 | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: polev1-basic
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_rew... | [
-0.03052711673080921,
0.01759573630988598,
0.004289268981665373,
0.010468591935932636,
0.04577666521072388,
-0.017882797867059708,
-0.022383838891983032,
-0.0189407579600811,
-0.034512028098106384,
0.082228884100914,
0.01715763844549656,
-0.009447388350963593,
0.010657398030161858,
0.02214... |
AnonymousSub/rule_based_roberta_twostagequadruplet_hier_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 | ---
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
... | [
-0.037594445049762726,
-0.002726753009483218,
-0.005340269301086664,
0.02558751590549946,
0.04562029987573624,
-0.02149583399295807,
-0.005286341067403555,
-0.027974002063274384,
-0.033313922584056854,
0.0664646178483963,
0.03233853727579117,
-0.02398896962404251,
0.02266896516084671,
0.00... |
AnonymousSub/rule_based_roberta_twostagetriplet_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... | 1 | null | ---
tags:
- stable diffusion
---
Just a place where i upload the models i mainly use for lora/lycrois training !!
I only upload models that arent already on hugging face btw.
all of the models here are availble on civitai -1 of them :3
Porn Merge
https://civitai.com/models/2661/uber-realistic-porn-merge-urpm | [
-0.033593956381082535,
-0.00008922258712118492,
0.0053933002054691315,
0.03837839514017105,
0.017026284709572792,
0.01050471793860197,
-0.0006325486465357244,
-0.011301186867058277,
-0.016076048836112022,
0.04513079300522804,
0.03258395940065384,
-0.012519203126430511,
0.002960937563329935,
... |
AnonymousSub/rule_based_roberta_twostagetriplet_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 | ---
library_name: ml-agents
tags:
- SnowballTarget
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SnowballTarget
---
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Tech... | [
-0.02828329987823963,
-0.004707020707428455,
-0.016997985541820526,
0.051070474088191986,
0.03675081208348274,
0.02622891031205654,
-0.00059535849140957,
-0.03414443880319595,
-0.02548058331012726,
0.047892093658447266,
0.024208268150687218,
-0.0065780277363955975,
0.017680827528238297,
0.... |
AnonymousSub/rule_based_twostagequadruplet_hier_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... | 1 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# rithwik-db/triplets-bert-base-cased-500
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be... | [
-0.037453629076480865,
-0.018909849226474762,
-0.01807265169918537,
0.050480350852012634,
0.009318224154412746,
0.04424569755792618,
-0.018721159547567368,
-0.006531078368425369,
-0.07023348659276962,
0.08275532722473145,
0.035757821053266525,
0.014658013358712196,
-0.0010553537867963314,
... |
AnonymousSub/rule_based_twostagetriplet_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 | ---
library_name: ml-agents
tags:
- Pyramids
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
... | [
-0.05074001103639603,
0.0026525619905442,
-0.00570543622598052,
0.05001210793852806,
0.025402365252375603,
0.030382176861166954,
-0.0096186688169837,
-0.023757755756378174,
-0.001413003890775144,
0.051507215946912766,
0.02517002820968628,
-0.011631401255726814,
0.006045855116099119,
0.0232... |
AnonymousSub/specter-bert-model_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... | 2 | null | Access to model Ekittl01/Illuminate is restricted and you are not in the authorized list. Visit https://huggingface.co/Ekittl01/Illuminate to ask for access. | [
-0.05237912759184837,
-0.0010006774682551622,
0.0184605922549963,
-0.005672452040016651,
0.06250742822885513,
0.014202989637851715,
-0.012166797183454037,
0.010219242423772812,
-0.07013595104217529,
0.05013732984662056,
0.046554479748010635,
-0.015464862808585167,
0.009386501275002956,
0.0... |
AnonymousSub/specter-bert-model_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... | 1 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: donut-sroie
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. -->
# donut-... | [
-0.03287471830844879,
-0.014434326440095901,
0.0005431219469755888,
0.046090636402368546,
0.03495170548558235,
-0.0016672040801495314,
0.01160935778170824,
-0.0009986239019781351,
-0.02716977708041668,
0.03301243111491203,
0.04469182714819908,
-0.025483030825853348,
0.024609839543700218,
0... |
AnonymousSub/unsup-consert-base_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:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-Cartpolev1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: ... | [
-0.030063381418585777,
0.018481897190213203,
0.00395924411714077,
0.008383668027818203,
0.04625282809138298,
-0.019863806664943695,
-0.025034433230757713,
-0.017564162611961365,
-0.0320294164121151,
0.08449835330247879,
0.020103711634874344,
-0.010275963693857193,
0.01750963367521763,
0.01... |
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 | Access to model pathanziyankhan989bba/Hackerdit is restricted and you are not in the authorized list. Visit https://huggingface.co/pathanziyankhan989bba/Hackerdit to ask for access. | [
-0.043499309569597244,
-0.015764569863677025,
0.0002944953739643097,
0.012611662968993187,
0.018155457451939583,
0.025760164484381676,
0.018328994512557983,
0.008787117898464203,
-0.04660160094499588,
0.039933547377586365,
0.05035063251852989,
-0.02367452345788479,
0.01842636615037918,
0.0... |
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 | ---
license: creativeml-openrail-m
---
https://civitai.com/models/32537/caulkinumv2ar-for-anime-style | [
-0.027006646618247032,
-0.012415727600455284,
0.001996599370613694,
0.022468088194727898,
0.05291103571653366,
-0.0008721596095710993,
0.003355555236339569,
0.005093255080282688,
-0.01566925272345543,
0.052300941199064255,
0.01931016705930233,
0.018101636320352554,
0.02215760014951229,
0.0... |
Anthos23/distilbert-base-uncased-finetuned-sst2 | [
"tf",
"tensorboard",
"distilbert",
"text-classification",
"transformers",
"generated_from_keras_callback",
"license:apache-2.0"
] | 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,
... | 21 | null | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: disfluency-large
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.... | [
-0.007031464949250221,
0.00474241329357028,
0.003660116344690323,
0.031824588775634766,
0.029724115505814552,
0.013846906833350658,
-0.004579317755997181,
-0.025691883638501167,
-0.03953901678323746,
0.053286317735910416,
0.031152743846178055,
-0.03191820904612541,
0.009960293769836426,
0.... |
Anthos23/my-awesome-model | [
"pytorch",
"tf",
"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,
"... | 30 | 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
... | [
-0.04580172523856163,
-0.000994302798062563,
-0.02210250124335289,
0.03241979703307152,
0.0434768907725811,
0.01793181337416172,
-0.018269408494234085,
-0.03061867505311966,
-0.037132181227207184,
0.06879270076751709,
0.021811917424201965,
0.0032871428411453962,
0.015243766829371452,
0.027... |
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 | ---
license: mit
---
### ahx-beta-4322d99 on Stable Diffusion
This is the `<ahx-beta-4322d99>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inf... | [
-0.02460065297782421,
-0.024068063125014305,
-0.03428306058049202,
0.04491801932454109,
0.008834751322865486,
0.018808014690876007,
0.0037937809247523546,
-0.011203670874238014,
-0.03256598487496376,
0.03784266486763954,
-0.005764711182564497,
-0.009459251537919044,
0.03036186657845974,
0.... |
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 | ---
tags:
- autotrain
- vision
- image-classification
datasets:
- cledoux42/autotrain-data-ethnicity-test_v003
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_t... | [
-0.0019602635875344276,
-0.024701548740267754,
0.01957062818109989,
0.04282400384545326,
0.05300883576273918,
0.0008054487989284098,
-0.02082425355911255,
0.003213590243831277,
-0.040434855967760086,
0.0701259970664978,
-0.0047316779382526875,
-0.004159212578088045,
0.009448561817407608,
0... |
ArBert/bert-base-uncased-finetuned-ner-gmm | [] | 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
datasets:
- odinsynth_sequence_dataset
model-index:
- name: odinsynth_encoder_decoder_test
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 c... | [
-0.051671795547008514,
-0.02666320465505123,
-0.009431181475520134,
0.030105678364634514,
0.036413416266441345,
0.020593123510479927,
-0.00989022757858038,
-0.02472067065536976,
-0.02991645224392414,
0.052678193897008896,
0.0317135751247406,
0.0090878801420331,
-0.008961412124335766,
0.061... |
ArBert/bert-base-uncased-finetuned-ner-kmeans | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"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... | 6 | 2023-04-09T04:42:33Z | ---
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
... | [
-0.037171587347984314,
-0.0031166651751846075,
-0.005354465916752815,
0.025716977193951607,
0.045924779027700424,
-0.021281719207763672,
-0.006179691758006811,
-0.02778601087629795,
-0.032493408769369125,
0.06659721583127975,
0.03217438980937004,
-0.022981517016887665,
0.022733893245458603,
... |
ArthurBaia/bert-base-portuguese-cased-finetuned-squad | [] | 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_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep5_lr4
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 remo... | [
-0.006446652114391327,
-0.008368848823010921,
-0.013217869214713573,
0.04626978561282158,
0.011332467198371887,
0.021267389878630638,
-0.024274829775094986,
-0.028483176603913307,
-0.03940264880657196,
0.06076725944876671,
0.006791470572352409,
-0.05538983643054962,
0.017572708427906036,
0... |
Atampy26/GPT-Glacier | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram... | 5 | null | ---
library_name: ml-agents
tags:
- Pyramids
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
... | [
-0.05098922550678253,
0.0024616688024252653,
-0.004784687422215939,
0.04939240962266922,
0.02414098009467125,
0.03196385130286217,
-0.010243828408420086,
-0.020746732130646706,
-0.0010886478703469038,
0.051413267850875854,
0.026013540104031563,
-0.013339818455278873,
0.00765705993399024,
0... |
Atlasky/turkish-negator-nn | [] | 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:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: roberta-base-value-determinator
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete i... | [
-0.03892875090241432,
-0.004130792338401079,
-0.00363153382204473,
0.013768613338470459,
0.02064780332148075,
0.040447767823934555,
0.002692057518288493,
-0.01852298714220524,
-0.03451496735215187,
0.05066273361444473,
0.04462467133998871,
-0.04185958579182625,
0.016784556210041046,
0.0397... |
Augustvember/WokkaBot7 | [] | 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 | 2023-04-09T07:31:43Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-hi
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. -->
# wh... | [
-0.039277154952287674,
-0.003974971827119589,
-0.005109038669615984,
0.029942158609628677,
0.034569162875413895,
0.01089317537844181,
-0.0037622114177793264,
0.003957115579396486,
-0.02316763810813427,
0.06817049533128738,
0.02656235173344612,
-0.028306150808930397,
0.015128876082599163,
0... |
AvatarXD/DialoGPT-medium-Blitzo | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 14 | null | ---
language:
- ru
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Russian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name:... | [
-0.034853462129831314,
-0.012970744632184505,
-0.011021245270967484,
0.04890323057770729,
0.05198104679584503,
0.019542161375284195,
-0.00496484711766243,
-0.010705726221203804,
-0.038582686334848404,
0.07774560153484344,
0.040403302758932114,
-0.0385647714138031,
0.003103332594037056,
0.0... |
Ayham/bert_gpt2_summarization_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 6 | 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
... | [
-0.03740331530570984,
-0.003221206134185195,
-0.00485705491155386,
0.025960244238376617,
0.04562121257185936,
-0.02129821479320526,
-0.005279135890305042,
-0.02776998281478882,
-0.0332413949072361,
0.06663025915622711,
0.03210941329598427,
-0.02367737516760826,
0.022720804437994957,
0.0011... |
Ayham/bert_roberta_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 3 | null | ---
datasets:
- hackathon-somos-nlp-2023/podcasts-ner-es
license: mit
language:
- es
pipeline_tag: text-generation
---
# Named-entity recognition for Spanish Podcasts
This model is a fine-tuned version for named-entity recognition of the Spanish [bertin-project/bertin-gpt-j-6B](https://huggingface.co/bertin-project/b... | [
-0.011681468226015568,
-0.010493069887161255,
0.006280986592173576,
0.037751246243715286,
0.04176119714975357,
0.03652669116854668,
-0.012540975585579872,
-0.00644256453961134,
-0.0296013243496418,
0.06172825023531914,
0.040226083248853683,
-0.016086021438241005,
-0.00419617909938097,
0.03... |
Ayham/bertgpt2_cnn | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"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: bigscience-bloom-rail-1.0
datasets:
- JosephusCheung/GuanacoDataset
language:
- am
metrics:
- character
library_name: flair
--- | [
-0.050087764859199524,
0.005972050130367279,
-0.0019503181101754308,
0.015939511358737946,
0.05710999667644501,
0.0025784973986446857,
-0.0036436619702726603,
0.0023123486898839474,
-0.04165170341730118,
0.030870243906974792,
0.02621591091156006,
0.04887561872601509,
0.029534749686717987,
... |
Ayham/roberta_distilgpt2_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | 2023-04-09T09:02:21Z | ---
license: mit
datasets:
- vicgalle/alpaca-gpt4
language:
- en
tags:
- gpt-j
- instruction-tuning
- alpaca
- gpt4
---
# GPT-J-6B instruction-tuned on Alpaca-GPT4
This model was finetuned on GPT-4 generations of the Alpaca prompts, using LoRA for 30.000 steps (batch size of 128), taking over 7 hours in four V100S.
... | [
-0.014654203318059444,
0.008372530341148376,
-0.00005859914017491974,
0.04846381023526192,
0.04210510849952698,
0.005323205608874559,
0.013936623930931091,
-0.008861510083079338,
-0.032207291573286057,
0.06646737456321716,
0.04490465670824051,
-0.03826252743601799,
0.01771971955895424,
0.0... |
Ayham/roberta_roberta_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 3 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-CartPole-v1-default
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
... | [
-0.029248271137475967,
0.01877676509320736,
0.0024444235023111105,
0.009496768936514854,
0.04268040880560875,
-0.01831076666712761,
-0.02009611763060093,
-0.016408780589699745,
-0.02936503291130066,
0.08483048528432846,
0.016411425545811653,
-0.008962602354586124,
0.017384719103574753,
0.0... |
Ayham/robertagpt2_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"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: creativeml-openrail-m
tags:
- text-to-image
---
### meryl-stryfe-20230408-17-adm-7k-4800-steps on Stable Diffusion via Dreambooth
#### model by NickKolok
This your the Stable Diffusion model fine-tuned the meryl-stryfe-20230408-17-adm-7k-4800-steps concept taught to Stable Diffusion with Dreambooth... | [
-0.038985610008239746,
-0.012098381295800209,
-0.03109484165906906,
0.016932398080825806,
0.030031971633434296,
0.022770529612898827,
-0.0038911737501621246,
-0.0004466928367037326,
-0.03683514893054962,
0.04450121149420738,
0.027171175926923752,
0.012485186569392681,
-0.015551785938441753,
... |
Ayham/xlmroberta_gpt2_summarization_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 9 | 2023-04-09T09:25:52Z | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: taxi-rl
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.56 +/- 2.71
... | [
-0.018349995836615562,
-0.013886015862226486,
-0.004899901337921619,
0.0275754164904356,
0.04766270890831947,
-0.0031463210470974445,
-0.020018449053168297,
0.007259556092321873,
-0.036614738404750824,
0.05291329324245453,
0.0196684580296278,
-0.0101062236353755,
0.011157515458762646,
0.02... |
Ayham/xlmroberta_large_gpt2_summarization_cnndm | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 12 | null | ### vicuna-7b
The repo contains the converted vicuna-7b model files.
The base model is from `decapoda-research/llama-7b-hf` and the delta model is from `lmsys/vicuna-7b-delta-v0`.
The conversion script is
```
python3 -m fastchat.model.apply_delta \
--base decapoda-research/llama-7b-hf \
--target /out... | [
-0.041311103850603104,
-0.04259050264954567,
-0.00736640440300107,
0.019651051610708237,
0.05585472658276558,
0.012784506194293499,
-0.0111629543825984,
-0.024477358907461166,
-0.006641970947384834,
0.042794421315193176,
0.03401407599449158,
-0.017344055697321892,
0.02478754334151745,
0.06... |
Ayham/xlnet_distilgpt2_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 13 | 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... | [
-0.04986244812607765,
-0.01599273271858692,
-0.008799736388027668,
0.036324501037597656,
0.041036978363990784,
0.003003810765221715,
-0.02152063138782978,
-0.010419701226055622,
-0.03782512992620468,
0.057006992399692535,
0.02484031394124031,
-0.0030156997963786125,
0.03160317242145538,
0.... |
Ayran/DialoGPT-medium-harry-potter-1-through-4-plus-6 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | 2023-04-09T10:05:33Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep8_lr2
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 remo... | [
-0.007512738462537527,
-0.010428998619318008,
-0.013232072815299034,
0.047232940793037415,
0.012525414116680622,
0.02203010953962803,
-0.020431363955140114,
-0.028378251940011978,
-0.03894549608230591,
0.06267578899860382,
0.0015712141757830977,
-0.05275484547019005,
0.020672770217061043,
... |
Ayta/Haha | [] | 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_trainer
metrics:
- bleu
model-index:
- name: en_to_kjven_translator
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. -->... | [
-0.028975022956728935,
-0.007307345047593117,
0.0024908643681555986,
0.03557118400931358,
0.028089873492717743,
-0.007206126116216183,
-0.01248682476580143,
-0.013681760989129543,
-0.042423758655786514,
0.046124979853630066,
-0.011536345817148685,
-0.04584995284676552,
-0.0054059321992099285... |
Ayu/Shiriro | [] | 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 | 2023-04-09T10:06:44Z | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: pixelcopterV1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
metrics... | [
-0.04257648438215256,
0.013500050641596317,
0.014347842894494534,
0.019971294328570366,
0.04903024435043335,
-0.014411233365535736,
-0.019121842458844185,
-0.02844921499490738,
-0.016302956268191338,
0.06578405201435089,
0.036537785083055496,
-0.007663143798708916,
0.008964958600699902,
-0... |
AyushPJ/ai-club-inductions-21-nlp-distilBERT | [
"pytorch",
"distilbert",
"question-answering",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | 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,
... | 8 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep8_lr3
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 remo... | [
-0.007823111489415169,
-0.010793948546051979,
-0.015742111951112747,
0.04789913073182106,
0.012739763595163822,
0.024004992097616196,
-0.02012871764600277,
-0.03016614355146885,
-0.039168886840343475,
0.06366261094808578,
0.0036945759784430265,
-0.05487324669957161,
0.019758077338337898,
0... |
AyushPJ/ai-club-inductions-21-nlp-roBERTa | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"generated_from_trainer",
"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... | 8 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep8_lr4
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 remo... | [
-0.009458120912313461,
-0.007068663835525513,
-0.014741400256752968,
0.047274332493543625,
0.011986417695879936,
0.02315722033381462,
-0.021207714453339577,
-0.030299663543701172,
-0.04000164568424225,
0.06278277933597565,
0.0017561311833560467,
-0.05572036653757095,
0.02255033329129219,
0... |
Azaghast/DistilBART-SCP-ParaSummarization | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"BartForConditionalGeneration"
],
"model_type": "bart",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 142,
"min_length": 56,
"no_repeat_ngr... | 8 | 2023-04-09T10:34:43Z | ---
license: mit
language:
- en
---
[Trained](https://ahxxm.com/179.moew/) on images labeled by myself.
2-step inference:
```python
from PIL import Image
import torch
import torch.nn as nn
import uform
path = "image.jpg"
# generate 768 dimension embeddings for an image
uf_model = uform.get_model("unum-cloud/uform-... | [
-0.01557843666523695,
-0.041646815836429596,
-0.006783714052289724,
0.04428393766283989,
0.04668545722961426,
0.023233652114868164,
-0.01245024986565113,
-0.0019550961442291737,
-0.022091196849942207,
0.05616403743624687,
0.03420694172382355,
-0.013066265732049942,
0.016587378457188606,
0.... |
Azaghast/DistilBERT-SCP-Class-Classification | [
"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,
... | 42 | 2023-04-09T10:35:48Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep8_lr5
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 remo... | [
-0.006992327515035868,
-0.0090097701177001,
-0.01262063067406416,
0.04708392918109894,
0.011885429732501507,
0.02183157205581665,
-0.02169250138103962,
-0.029458487406373024,
-0.03906376287341118,
0.06180056929588318,
0.003770785639062524,
-0.05477246642112732,
0.020129278302192688,
0.0453... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.