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text-generation | transformers |
<p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/641b435ba5f876fe30c5ae0a/Ds-Nf-6VvLdpUx_l0Yiu_.png" alt="" style="width: 95%; max-height: 750px;">
</p>
## Metrics.
<p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/641b435ba5f876fe30c5ae0a/clM... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "datasets": ["hiyouga/glaive-function-calling-v2-sharegpt", "NickyNicky/function-calling_chatml_gemma_v1"], "model": ["google/gemma-1.1-2b-it"], "widget": [{"text": "<bos><start_of_turn>system\nYou are a helpful AI assistant.<end_of_turn>\n<s... | NickyNicky/gemma-1.1-2b-it_oasst_format_chatML_unsloth_V1_function_calling_V2 | null | [
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... | null | 2024-04-13T18:28:49+00:00 | [] | [
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|
<p align="center">
<img src="URL alt="" style="width: 95%; max-height: 750px;">
</p>
## Metrics.
<p align="center">
<img src="URL alt="" style="width: 95%; max-height: 750px;">
</p>
<p align="center">
<img src="URL alt="" style="width: 95%; max-height: 750px;">
</p>
## Take dataset.
## Dataset format... | [
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image-classification | transformers |
<!-- 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. -->
# Psoriasis-Project-M-swinv2-base-patch4-window12-192-22k
This model is a fine-tuned version of [microsoft/swinv2-base-patch4-wind... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/swinv2-base-patch4-window12-192-22k", "model-index": [{"name": "Psoriasis-Project-M-swinv2-base-patch4-window12-192-22k", "results": []}]} | ahmedesmail16/Psoriasis-Project-M-swinv2-base-patch4-window12-192-22k | null | [
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| Psoriasis-Project-M-swinv2-base-patch4-window12-192-22k
=======================================================
This model is a fine-tuned version of microsoft/swinv2-base-patch4-window12-192-22k on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2385
* Accuracy: 0.9167
Mode... | [
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text2text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": ["trl", "sft"]} | Rutts07/t5-ai-human-gen | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-to-image | null |
# LoRA model of Bianca Eleanor/エレオノール・ビアンカ (Maou Gakuin no Futekigousha)
## What Is This?
This is the LoRA model of waifu Bianca Eleanor/エレオノール・ビアンカ (Maou Gakuin no Futekigousha).
## How Is It Trained?
* This model is trained with [kohya-ss/sd-scripts](https://github.com/kohya-ss/sd-scripts), and the test images a... | {"license": "mit", "tags": ["art", "not-for-all-audiences"], "datasets": ["CyberHarem/bianca_eleanor_maougakuinnofutekigousha", "BangumiBase/maougakuinnofutekigousha"], "pipeline_tag": "text-to-image"} | CyberHarem/bianca_eleanor_maougakuinnofutekigousha | null | [
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| LoRA model of Bianca Eleanor/エレオノール・ビアンカ (Maou Gakuin no Futekigousha)
======================================================================
What Is This?
-------------
This is the LoRA model of waifu Bianca Eleanor/エレオノール・ビアンカ (Maou Gakuin no Futekigousha).
How Is It Trained?
------------------
* This model i... | [] | [
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null | null |
<!-- 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. -->
# wav2vecvlora_ctc_zero_infinity
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebo... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "facebook/wav2vec2-base-960h", "model-index": [{"name": "wav2vecvlora_ctc_zero_infinity", "results": []}]} | charris/wav2vecvlora_ctc_zero_infinity | null | [
"tensorboard",
"safetensors",
"generated_from_trainer",
"base_model:facebook/wav2vec2-base-960h",
"license:apache-2.0",
"region:us"
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#tensorboard #safetensors #generated_from_trainer #base_model-facebook/wav2vec2-base-960h #license-apache-2.0 #region-us
|
# wav2vecvlora_ctc_zero_infinity
This model is a fine-tuned version of facebook/wav2vec2-base-960h on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Trai... | [
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token-classification | transformers |
<!-- 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. -->
# bert-finetuned-ner
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the foll... | {"tags": ["generated_from_trainer"], "model-index": [{"name": "bert-finetuned-ner", "results": []}]} | Kkkelsey/bert-finetuned-ner | null | [
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"gpt2",
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"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
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"region:us"
] | null | 2024-04-13T18:33:03+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #gpt2 #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| bert-finetuned-ner
==================
This model is a fine-tuned version of [](URL on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1575
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More informati... | [
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text2text-generation | transformers |
<!-- 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. -->
# new_output
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves ... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "t5-small", "model-index": [{"name": "new_output", "results": []}]} | aprab/new_output | null | [
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| new\_output
===========
This model is a fine-tuned version of t5-small on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0280
* Rouge1: 0.2245
* Rouge2: 0.1862
* Rougel: 0.2241
* Rougelsum: 0.2241
Model description
-----------------
More information needed
Intended uses... | [
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null | peft |
<!-- 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. -->
# organc-deit-base-finetuned
This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/faceboo... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "datasets": ["medmnist-v2"], "metrics": ["accuracy", "precision", "recall", "f1"], "base_model": "facebook/deit-base-patch16-224", "model-index": [{"name": "organc-deit-base-finetuned", "results": []}]} | selmamalak/organc-deit-base-finetuned | null | [
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| organc-deit-base-finetuned
==========================
This model is a fine-tuned version of facebook/deit-base-patch16-224 on the medmnist-v2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2795
* Accuracy: 0.9240
* Precision: 0.9199
* Recall: 0.9123
* F1: 0.9154
Model description
----... | [
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summarization | peft |
# Model Card
There are facebook/bard-large-cnn LoRA finetuned model for dialogue summarization.
This LoRA weights trained on [dialogue sum augmented dataset](https://huggingface.co/datasets/doublecringe123/dialoguesum-npc-dialoguesum-stemmed-augmented)
## Model Details
```
cfg.lora_params = {
'target_modules':... | {"language": ["en"], "library_name": "peft", "datasets": ["doublecringe123/dialoguesum-npc-dialoguesum-stemmed-augmented"], "metrics": ["rouge"], "pipeline_tag": "summarization"} | doublecringe123/bardt-large-cnn-dialoguesum-booksum-lora | null | [
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|
# Model Card
There are facebook/bard-large-cnn LoRA finetuned model for dialogue summarization.
This LoRA weights trained on dialogue sum augmented dataset
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### Model Description
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text-to-image | null |
# LoRA model of Rudewell Emilia/エミリア・ルードウェル (Maou Gakuin no Futekigousha)
## What Is This?
This is the LoRA model of waifu Rudewell Emilia/エミリア・ルードウェル (Maou Gakuin no Futekigousha).
## How Is It Trained?
* This model is trained with [kohya-ss/sd-scripts](https://github.com/kohya-ss/sd-scripts), and the test images... | {"license": "mit", "tags": ["art", "not-for-all-audiences"], "datasets": ["CyberHarem/rudewell_emilia_maougakuinnofutekigousha", "BangumiBase/maougakuinnofutekigousha"], "pipeline_tag": "text-to-image"} | CyberHarem/rudewell_emilia_maougakuinnofutekigousha | null | [
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"region:us"
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#art #not-for-all-audiences #text-to-image #dataset-CyberHarem/rudewell_emilia_maougakuinnofutekigousha #dataset-BangumiBase/maougakuinnofutekigousha #license-mit #region-us
| LoRA model of Rudewell Emilia/エミリア・ルードウェル (Maou Gakuin no Futekigousha)
=======================================================================
What Is This?
-------------
This is the LoRA model of waifu Rudewell Emilia/エミリア・ルードウェル (Maou Gakuin no Futekigousha).
How Is It Trained?
------------------
* This mode... | [] | [
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] |
text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | nagayoshi3/gpt_0.125B_global_step400 | null | [
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"text-generation",
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"autotrain_compatible",
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"1910.09700"
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#transformers #safetensors #gpt2 #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | peft |
<!-- 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. -->
# falcon-1b-code-generation
This model is a fine-tuned version of [petals-team/falcon-rw-1b](https://huggingface.co/petals-team/fa... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["code_search_net"], "base_model": "petals-team/falcon-rw-1b", "model-index": [{"name": "falcon-1b-code-generation", "results": []}]} | Katochh/falcon-1b-code-generation | null | [
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| falcon-1b-code-generation
=========================
This model is a fine-tuned version of petals-team/falcon-rw-1b on the code\_search\_net dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9849
Model description
-----------------
More information needed
Intended uses & limitations
-... | [
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text-to-image | null |
# LoRA model of Izabella/イザベラ (Maou Gakuin no Futekigousha)
## What Is This?
This is the LoRA model of waifu Izabella/イザベラ (Maou Gakuin no Futekigousha).
## How Is It Trained?
* This model is trained with [kohya-ss/sd-scripts](https://github.com/kohya-ss/sd-scripts), and the test images are generated with [a1111's... | {"license": "mit", "tags": ["art", "not-for-all-audiences"], "datasets": ["CyberHarem/izabella_maougakuinnofutekigousha", "BangumiBase/maougakuinnofutekigousha"], "pipeline_tag": "text-to-image"} | CyberHarem/izabella_maougakuinnofutekigousha | null | [
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"license:mit",
"region:us"
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#art #not-for-all-audiences #text-to-image #dataset-CyberHarem/izabella_maougakuinnofutekigousha #dataset-BangumiBase/maougakuinnofutekigousha #license-mit #region-us
| LoRA model of Izabella/イザベラ (Maou Gakuin no Futekigousha)
=========================================================
What Is This?
-------------
This is the LoRA model of waifu Izabella/イザベラ (Maou Gakuin no Futekigousha).
How Is It Trained?
------------------
* This model is trained with kohya-ss/sd-scripts, and... | [] | [
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] |
text-to-image | null |
# LoRA model of Bianca Zeshia/ゼシア・ビアンカ (Maou Gakuin no Futekigousha)
## What Is This?
This is the LoRA model of waifu Bianca Zeshia/ゼシア・ビアンカ (Maou Gakuin no Futekigousha).
## How Is It Trained?
* This model is trained with [kohya-ss/sd-scripts](https://github.com/kohya-ss/sd-scripts), and the test images are gener... | {"license": "mit", "tags": ["art", "not-for-all-audiences"], "datasets": ["CyberHarem/bianca_zeshia_maougakuinnofutekigousha", "BangumiBase/maougakuinnofutekigousha"], "pipeline_tag": "text-to-image"} | CyberHarem/bianca_zeshia_maougakuinnofutekigousha | null | [
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"license:mit",
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| LoRA model of Bianca Zeshia/ゼシア・ビアンカ (Maou Gakuin no Futekigousha)
==================================================================
What Is This?
-------------
This is the LoRA model of waifu Bianca Zeshia/ゼシア・ビアンカ (Maou Gakuin no Futekigousha).
How Is It Trained?
------------------
* This model is trained wi... | [] | [
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image-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | mulsi/fruit-vegetable-clip-vit-base-patch32 | null | [
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"1910.09700"
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#transformers #safetensors #clip #image-classification #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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For another candidate version of 2 epoches - https://huggingface.co/CausalLM/35b-beta2ep - somehow overfitting?
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text-generation | transformers | Tokenizer is different from cohere - and chat template is ChatML - fully fine-tuned at 128K+ ~ 30M entries long, web crawl input, GPT-4-32k/3.5-16k output, synthetic dataset - 1 epoch
For another candidate version of 1 epoch - https://huggingface.co/CausalLM/35b-beta - somehow less overfitting?
No loras, no quants, n... | {"language": ["en", "zh", "ja", "de"], "license": "gpl-3.0", "datasets": ["JosephusCheung/GuanacoDataset", "meta-math/MetaMathQA", "jondurbin/airoboros-3.1", "WizardLM/WizardLM_evol_instruct_V2_196k", "RyokoAI/ShareGPT52K", "RyokoAI/Fandom23K", "milashkaarshif/MoeGirlPedia_wikitext_raw_archive", "wikipedia", "wiki_ling... | CausalLM/35b-beta2ep | null | [
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For another candidate version of 1 epoch - URL - somehow less overfitting?
No loras, no quants, no tricks.
This one is not "very 128k... | [] | [
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text-generation | transformers | ## TBA
Tokenizer is different from cohere - and chat template is ChatML - fully fine-tuned at 128K+
No loras, no quants, no tricks, 30M+ sft data.
Pressure Testing from: https://github.com/LeonEricsson/llmcontext
![image/png](https://cdn-uploads.huggingface.co/production/uploads/63468a143ea42ee2cb49ddd1/2XbONpyTeMH... | {"language": ["en", "zh", "ja", "de"], "license": "gpl-3.0", "datasets": ["JosephusCheung/GuanacoDataset", "meta-math/MetaMathQA", "jondurbin/airoboros-3.1", "WizardLM/WizardLM_evol_instruct_V2_196k", "RyokoAI/ShareGPT52K", "RyokoAI/Fandom23K", "milashkaarshif/MoeGirlPedia_wikitext_raw_archive", "wikipedia", "wiki_ling... | CausalLM/35b-beta-long | null | [
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Tokenizer is different from cohere - and chat template is ChatML - fully fine-tuned at 128K+
No loras, no quants, no tricks, 30M+ sft data.
Pressure Testing from: URL
!image/png | [
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null | diffusers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
... | {"library_name": "diffusers"} | ManuD/test | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | Kkkelsey/mlma | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/jukofyork/Eurus-70b-nca-fixed
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/Eurus-70b-n... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["reasoning", "preference_learning", "nca"], "datasets": ["openbmb/UltraInteract_pair", "openbmb/UltraFeedback"], "base_model": "jukofyork/Eurus-70b-nca-fixed", "quantized_by": "mradermacher"} | mradermacher/Eurus-70b-nca-fixed-i1-GGUF | null | [
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| About
-----
weighted/imatrix quants of URL
static quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
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text-to-image | null |
# LoRA model of Great Spirit Reno/大精霊レノ (Maou Gakuin no Futekigousha)
## What Is This?
This is the LoRA model of waifu Great Spirit Reno/大精霊レノ (Maou Gakuin no Futekigousha).
## How Is It Trained?
* This model is trained with [kohya-ss/sd-scripts](https://github.com/kohya-ss/sd-scripts), and the test images are gen... | {"license": "mit", "tags": ["art", "not-for-all-audiences"], "datasets": ["CyberHarem/great_spirit_reno_maougakuinnofutekigousha", "BangumiBase/maougakuinnofutekigousha"], "pipeline_tag": "text-to-image"} | CyberHarem/great_spirit_reno_maougakuinnofutekigousha | null | [
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"dataset:BangumiBase/maougakuinnofutekigousha",
"license:mit",
"region:us"
] | null | 2024-04-13T18:51:29+00:00 | [] | [] | TAGS
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| LoRA model of Great Spirit Reno/大精霊レノ (Maou Gakuin no Futekigousha)
===================================================================
What Is This?
-------------
This is the LoRA model of waifu Great Spirit Reno/大精霊レノ (Maou Gakuin no Futekigousha).
How Is It Trained?
------------------
* This model is trained... | [] | [
"TAGS\n#art #not-for-all-audiences #text-to-image #dataset-CyberHarem/great_spirit_reno_maougakuinnofutekigousha #dataset-BangumiBase/maougakuinnofutekigousha #license-mit #region-us \n"
] | [
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] |
text-to-image | null |
# LoRA model of Ilioroagu Misa/ミサ・イリオローグ (Maou Gakuin no Futekigousha)
## What Is This?
This is the LoRA model of waifu Ilioroagu Misa/ミサ・イリオローグ (Maou Gakuin no Futekigousha).
## How Is It Trained?
* This model is trained with [kohya-ss/sd-scripts](https://github.com/kohya-ss/sd-scripts), and the test images are g... | {"license": "mit", "tags": ["art", "not-for-all-audiences"], "datasets": ["CyberHarem/ilioroagu_misa_maougakuinnofutekigousha", "BangumiBase/maougakuinnofutekigousha"], "pipeline_tag": "text-to-image"} | CyberHarem/ilioroagu_misa_maougakuinnofutekigousha | null | [
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"license:mit",
"region:us"
] | null | 2024-04-13T18:54:02+00:00 | [] | [] | TAGS
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| LoRA model of Ilioroagu Misa/ミサ・イリオローグ (Maou Gakuin no Futekigousha)
====================================================================
What Is This?
-------------
This is the LoRA model of waifu Ilioroagu Misa/ミサ・イリオローグ (Maou Gakuin no Futekigousha).
How Is It Trained?
------------------
* This model is trai... | [] | [
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] | [
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] |
text-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
device = "cuda" # the device to load the model onto
model = AutoModelForCausalLM.from_pretrained("armaniii/llama-argument-classification")... | {"library_name": "transformers", "pipeline_tag": "text-classification"} | armaniii/llama-argument-classification | null | [
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"text-generation",
"text-classification",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-13T18:57:13+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #text-classification #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- Licens... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | ManuD/tts_test | null | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T18:58:05+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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"## Model Details",
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/ibivibiv/strix-rufipes-70b
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/strix-rufipes-... | {"language": ["en"], "license": "llama2", "library_name": "transformers", "tags": ["logic", "planning"], "base_model": "ibivibiv/strix-rufipes-70b", "quantized_by": "mradermacher"} | mradermacher/strix-rufipes-70b-i1-GGUF | null | [
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"logic",
"planning",
"en",
"base_model:ibivibiv/strix-rufipes-70b",
"license:llama2",
"endpoints_compatible",
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"en"
] | TAGS
#transformers #gguf #logic #planning #en #base_model-ibivibiv/strix-rufipes-70b #license-llama2 #endpoints_compatible #region-us
| About
-----
weighted/imatrix quants of URL
static quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
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] |
text-generation | transformers |
[<img src="https://i.ibb.co/5Lbwyr1/dicta-logo.jpg" width="300px"/>](https://dicta.org.il)
# Model Card for DictaLM-2.0-Instruct
The DictaLM-2.0-Instruct Large Language Model (LLM) is an instruct fine-tuned version of the [DictaLM-2.0](https://huggingface.co/dicta-il/dictalm2.0) generative model using a variety of ... | {"language": ["en", "he"], "license": "apache-2.0", "tags": ["instruction-tuned"], "pipeline_tag": "text-generation", "base_model": "dicta-il/dictalm2.0", "inference": false} | dicta-il/dictalm2.0-instruct-AWQ | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"instruction-tuned",
"conversational",
"en",
"he",
"base_model:dicta-il/dictalm2.0",
"license:apache-2.0",
"autotrain_compatible",
"text-generation-inference",
"4-bit",
"region:us"
] | null | 2024-04-13T18:59:11+00:00 | [] | [
"en",
"he"
] | TAGS
#transformers #safetensors #mistral #text-generation #instruction-tuned #conversational #en #he #base_model-dicta-il/dictalm2.0 #license-apache-2.0 #autotrain_compatible #text-generation-inference #4-bit #region-us
|
<img src="https://i.URL width="300px"/>
# Model Card for DictaLM-2.0-Instruct
The DictaLM-2.0-Instruct Large Language Model (LLM) is an instruct fine-tuned version of the DictaLM-2.0 generative model using a variety of conversation datasets.
For full details of this model please read our release blog post.
This m... | [
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image-classification | transformers |
<!-- 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. -->
# Psoriasis-Project-Aug-M2-swinv2-base-patch4-window12-192-22k
This model is a fine-tuned version of [microsoft/swinv2-base-patch4... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/swinv2-base-patch4-window12-192-22k", "pipeline_tag": "image-classification", "model-index": [{"name": "Psoriasis-Project-Aug-M2-swinv2-base-patch4-window12-192-22k", "results": []}]} | ahmedesmail16/Psoriasis-Project-Aug-M2-swinv2-base-patch4-window12-192-22k | null | [
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"license:apache-2.0",
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| Psoriasis-Project-Aug-M2-swinv2-base-patch4-window12-192-22k
============================================================
This model is a fine-tuned version of microsoft/swinv2-base-patch4-window12-192-22k on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0088
* Accuracy: 1.0... | [
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
model = load_from_hub(repo_id="spietari/q-Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.m... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.54 +/... | spietari/q-Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-13T19:00:41+00:00 | [] | [] | TAGS
#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
## Usage
model = load_from_hub(repo_id="spietari/q-Taxi-v3", filename="URL")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = URL(model["env_id"])
| [
"# Q-Learning Agent playing1 Taxi-v3\n This is a trained model of a Q-Learning agent playing Taxi-v3 .\n\n ## Usage\n\n model = load_from_hub(repo_id=\"spietari/q-Taxi-v3\", filename=\"URL\")\n\n # Don't forget to check if you need to add additional attributes (is_slippery=False etc)\n env = URL(model[\"env_id... | [
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null | transformers |
<!-- 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. -->
# Swin-Bert_Mimic
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the followi... | {"tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "Swin-Bert_Mimic", "results": []}]} | ChayanM/Swin-Bert_Mimic | null | [
"transformers",
"safetensors",
"vision-encoder-decoder",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T19:02:31+00:00 | [] | [] | TAGS
#transformers #safetensors #vision-encoder-decoder #generated_from_trainer #endpoints_compatible #region-us
| Swin-Bert\_Mimic
================
This model is a fine-tuned version of [](URL on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1025
* Rouge1: 35.8104
* Rouge2: 22.5915
* Rougel: 34.3056
* Rougelsum: 35.1416
* Gen Len: 21.289
Model description
-----------------
More info... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 20",
"### Trainin... | [
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text-generation | transformers |
<!-- 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. -->
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axo... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "pytorch", "results": []}]} | KolaGang/finals | null | [
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"conversational",
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-13T19:03:09+00:00 | [] | [] | TAGS
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| <img src="URL alt="Built with Axolotl" width="200" height="32"/>
See axolotl config
axolotl version: '0.4.0'
pytorch
=======
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7778
Model descripti... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-06\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 8\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 256\n... | [
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reinforcement-learning | ml-agents |
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
... | {"library_name": "ml-agents", "tags": ["Huggy", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Huggy"]} | nachoglezmur/ppo-Huggy | null | [
"ml-agents",
"tensorboard",
"onnx",
"Huggy",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Huggy",
"region:us"
] | null | 2024-04-13T19:03:10+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us
|
# ppo Agent playing Huggy
This is a trained model of a ppo agent playing Huggy
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you te... | [
"# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* wh... | [
"TAGS\n#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us \n",
"# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n W... | [
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201
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"TAGS\n#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us \n# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrot... |
null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | gkMSDA/Llama-2-7b-FinChatGTP298_DJ30_Model_3v1 | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T19:07:04+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Devel... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/saucam/Pyrhea-72B
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/Pyrhea-72B-GGUF
## Usag... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["merge", "mergekit", "davidkim205/Rhea-72b-v0.5", "abacusai/Smaug-72B-v0.1"], "base_model": "saucam/Pyrhea-72B", "quantized_by": "mradermacher"} | mradermacher/Pyrhea-72B-i1-GGUF | null | [
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"license:apache-2.0",
"endpoints_compatible",
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"en"
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| About
-----
weighted/imatrix quants of URL
static quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
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] |
null | adapter-transformers |
# Adapter `BigTMiami/BB_seq_bn_P_3` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_split_25M_reviews_20_percent_condensed](https://huggingface.co/datasets/BigTMiami/amazon_split_25M_reviews_20_percent_condensed/) dataset and includes a predi... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_split_25M_reviews_20_percent_condensed"]} | BigTMiami/BB_seq_bn_P_3 | null | [
"adapter-transformers",
"roberta",
"dataset:BigTMiami/amazon_split_25M_reviews_20_percent_condensed",
"region:us"
] | null | 2024-04-13T19:09:49+00:00 | [] | [] | TAGS
#adapter-transformers #roberta #dataset-BigTMiami/amazon_split_25M_reviews_20_percent_condensed #region-us
|
# Adapter 'BigTMiami/BB_seq_bn_P_3' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_split_25M_reviews_20_percent_condensed dataset and includes a prediction head for masked lm.
This adapter was created for usage with the Adapters library.
## Usage
First, install 'a... | [
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"## Usage\n\nFir... | [
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null | null |
# fuddy23/NeuralExperiment-7b-MagicCoder-v7.5-Q6_K-GGUF
This model was converted to GGUF format from [`Kukedlc/NeuralExperiment-7b-MagicCoder-v7.5`](https://huggingface.co/Kukedlc/NeuralExperiment-7b-MagicCoder-v7.5) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) ... | {"license": "apache-2.0", "tags": ["llama-cpp", "gguf-my-repo"], "datasets": ["microsoft/orca-math-word-problems-200k", "ise-uiuc/Magicoder-Evol-Instruct-110K", "Vezora/Tested-22k-Python-Alpaca"]} | fuddy23/NeuralExperiment-7b-MagicCoder-v7.5-Q6_K-GGUF | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"dataset:microsoft/orca-math-word-problems-200k",
"dataset:ise-uiuc/Magicoder-Evol-Instruct-110K",
"dataset:Vezora/Tested-22k-Python-Alpaca",
"license:apache-2.0",
"region:us"
] | null | 2024-04-13T19:12:12+00:00 | [] | [] | TAGS
#gguf #llama-cpp #gguf-my-repo #dataset-microsoft/orca-math-word-problems-200k #dataset-ise-uiuc/Magicoder-Evol-Instruct-110K #dataset-Vezora/Tested-22k-Python-Alpaca #license-apache-2.0 #region-us
|
# fuddy23/NeuralExperiment-7b-MagicCoder-v7.5-Q6_K-GGUF
This model was converted to GGUF format from 'Kukedlc/NeuralExperiment-7b-MagicCoder-v7.5' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL serv... | [
"# fuddy23/NeuralExperiment-7b-MagicCoder-v7.5-Q6_K-GGUF\nThis model was converted to GGUF format from 'Kukedlc/NeuralExperiment-7b-MagicCoder-v7.5' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
"## Use with URL\n\nInstall URL through brew.\n\n\nInv... | [
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"# fuddy23/NeuralExperiment-7b-MagicCoder-v7.5-Q6_K-GGUF\nThis model was converted to GGUF format from '... | [
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"TAGS\n#gguf #llama-cpp #gguf-my-repo #dataset-microsoft/orca-math-word-problems-200k #dataset-ise-uiuc/Magicoder-Evol-Instruct-110K #dataset-Vezora/Tested-22k-Python-Alpaca #license-apache-2.0 #region-us \n# fuddy23/NeuralExperiment-7b-MagicCoder-v7.5-Q6_K-GGUF\nThis model was converted to GGUF format from 'Kukedl... |
text-to-image | null |
# LoRA model of Necron Sasha/サーシャ・ネクロン (Maou Gakuin no Futekigousha)
## What Is This?
This is the LoRA model of waifu Necron Sasha/サーシャ・ネクロン (Maou Gakuin no Futekigousha).
## How Is It Trained?
* This model is trained with [kohya-ss/sd-scripts](https://github.com/kohya-ss/sd-scripts), and the test images are gener... | {"license": "mit", "tags": ["art", "not-for-all-audiences"], "datasets": ["CyberHarem/necron_sasha_maougakuinnofutekigousha", "BangumiBase/maougakuinnofutekigousha"], "pipeline_tag": "text-to-image"} | CyberHarem/necron_sasha_maougakuinnofutekigousha | null | [
"art",
"not-for-all-audiences",
"text-to-image",
"dataset:CyberHarem/necron_sasha_maougakuinnofutekigousha",
"dataset:BangumiBase/maougakuinnofutekigousha",
"license:mit",
"region:us"
] | null | 2024-04-13T19:12:45+00:00 | [] | [] | TAGS
#art #not-for-all-audiences #text-to-image #dataset-CyberHarem/necron_sasha_maougakuinnofutekigousha #dataset-BangumiBase/maougakuinnofutekigousha #license-mit #region-us
| LoRA model of Necron Sasha/サーシャ・ネクロン (Maou Gakuin no Futekigousha)
==================================================================
What Is This?
-------------
This is the LoRA model of waifu Necron Sasha/サーシャ・ネクロン (Maou Gakuin no Futekigousha).
How Is It Trained?
------------------
* This model is trained wi... | [] | [
"TAGS\n#art #not-for-all-audiences #text-to-image #dataset-CyberHarem/necron_sasha_maougakuinnofutekigousha #dataset-BangumiBase/maougakuinnofutekigousha #license-mit #region-us \n"
] | [
66
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"TAGS\n#art #not-for-all-audiences #text-to-image #dataset-CyberHarem/necron_sasha_maougakuinnofutekigousha #dataset-BangumiBase/maougakuinnofutekigousha #license-mit #region-us \n"
] |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"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": "LunarL... | JoaoPinto/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-13T19:16:38+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
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] |
null | transformers |
# Mantis: Interleaved Multi-Image Instruction Tuning
**Mantis** is a multimodal conversational AI model that can chat with users about images and text. It's optimized for multi-image reasoning, where interleaved text and images can be used fed as the input to generate responses.
Mantis is trained on the newly curate... | {"language": ["en"], "license": "apache-2.0", "tags": ["Mantis", "VLM", "LMM", "Multimodal LLM", "llava"], "base_model": "llava-hf/llava-1.5-7b-hf", "model-index": [{"name": "Mantis-llava-7b", "results": []}]} | TIGER-Lab/Mantis-llava-7b | null | [
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"base_model:llava-hf/llava-1.5-7b-hf",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T19:19:14+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #llava #pretraining #Mantis #VLM #LMM #Multimodal LLM #en #base_model-llava-hf/llava-1.5-7b-hf #license-apache-2.0 #endpoints_compatible #region-us
|
# Mantis: Interleaved Multi-Image Instruction Tuning
Mantis is a multimodal conversational AI model that can chat with users about images and text. It's optimized for multi-image reasoning, where interleaved text and images can be used fed as the input to generate responses.
Mantis is trained on the newly curated da... | [
"# Mantis: Interleaved Multi-Image Instruction Tuning\n\nMantis is a multimodal conversational AI model that can chat with users about images and text. It's optimized for multi-image reasoning, where interleaved text and images can be used fed as the input to generate responses.\n\nMantis is trained on the newly cu... | [
"TAGS\n#transformers #safetensors #llava #pretraining #Mantis #VLM #LMM #Multimodal LLM #en #base_model-llava-hf/llava-1.5-7b-hf #license-apache-2.0 #endpoints_compatible #region-us \n",
"# Mantis: Interleaved Multi-Image Instruction Tuning\n\nMantis is a multimodal conversational AI model that can chat with user... | [
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"TAGS\n#transformers #safetensors #llava #pretraining #Mantis #VLM #LMM #Multimodal LLM #en #base_model-llava-hf/llava-1.5-7b-hf #license-apache-2.0 #endpoints_compatible #region-us \n# Mantis: Interleaved Multi-Image Instruction Tuning\n\nMantis is a multimodal conversational AI model that can chat with users abou... |
reinforcement-learning | null |
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="cansakiroglu/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additiona... | {"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": ... | cansakiroglu/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-13T19:26:24+00:00 | [] | [] | TAGS
#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
## Usage
| [
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] |
null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | ManuD/tts_test_processor | null | [
"transformers",
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"region:us"
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|
# Model Card for Model ID
## Model Details
### Model Description
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null | null |
## Matter 7B - 0.2 - DPO - GGUF (Mistral 7B Finetune)
- This is GGUF quantized evrsion of [Matter-7b-0.2-DPO](https://huggingface.co/0-hero/Matter-0.2-7B-DPO), which is Mistral 7B Finetune
- [Matter-7b-0.2-DPO](https://huggingface.co/0-hero/Matter-0.2-7B-DPO) is the DPO version of [Matter 7B](https://huggingface.co/0-... | {"language": ["en"], "license": "apache-2.0", "datasets": ["0-hero/Matter-0.2-alpha"], "base_model": "0-hero/Matter-0.2-7B-DPO"} | QuantFactory/Matter-0.2-7B-DPO-GGUF | null | [
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"dataset:0-hero/Matter-0.2-alpha",
"base_model:0-hero/Matter-0.2-7B-DPO",
"license:apache-2.0",
"region:us"
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"en"
] | TAGS
#gguf #en #dataset-0-hero/Matter-0.2-alpha #base_model-0-hero/Matter-0.2-7B-DPO #license-apache-2.0 #region-us
|
## Matter 7B - 0.2 - DPO - GGUF (Mistral 7B Finetune)
- This is GGUF quantized evrsion of Matter-7b-0.2-DPO, which is Mistral 7B Finetune
- Matter-7b-0.2-DPO is the DPO version of Matter 7B fine-tuned on the Matter dataset, which is curated from over 35 datsets analyzing >6B tokens
### Training
Prompt format: This ... | [
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null | adapter-transformers |
# Adapter `BigTMiami/BB_seq_bn_C_20` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_helpfulness](https://huggingface.co/datasets/BigTMiami/amazon_helpfulness/) dataset and includes a prediction head for classification.
This adapter was crea... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_helpfulness"]} | BigTMiami/BB_seq_bn_C_20 | null | [
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#adapter-transformers #roberta #dataset-BigTMiami/amazon_helpfulness #region-us
|
# Adapter 'BigTMiami/BB_seq_bn_C_20' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_helpfulness dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters library.
## Usage
First, install 'adapters':
Now, the... | [
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null | peft |
<!-- 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. -->
# OCI-DS-6.7B-schema_2
This model is a fine-tuned version of [m-a-p/OpenCodeInterpreter-DS-6.7B](https://huggingface.co/m-a-p/Open... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "m-a-p/OpenCodeInterpreter-DS-6.7B", "model-index": [{"name": "OCI-DS-6.7B-schema_2", "results": []}]} | jdeklerk10/OCI-DS-6.7B-schema_2 | null | [
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"region:us"
] | null | 2024-04-13T19:31:58+00:00 | [] | [] | TAGS
#peft #safetensors #trl #sft #generated_from_trainer #base_model-m-a-p/OpenCodeInterpreter-DS-6.7B #license-apache-2.0 #region-us
| OCI-DS-6.7B-schema\_2
=====================
This model is a fine-tuned version of m-a-p/OpenCodeInterpreter-DS-6.7B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0000
Model description
-----------------
More information needed
Intended uses & limitations
-----------... | [
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text-generation | mlx |
# mlx-community/Qwen1.5-72B-4bit
This model was converted to MLX format from [`Qwen/Qwen1.5-72B`]() using mlx-lm version **0.9.0**.
Refer to the [original model card](https://huggingface.co/Qwen/Qwen1.5-72B) for more details on the model.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import lo... | {"language": ["en"], "license": "other", "tags": ["pretrained", "mlx"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/Qwen1.5-72B/blob/main/LICENSE", "pipeline_tag": "text-generation"} | mlx-community/Qwen1.5-72B-4bit | null | [
"mlx",
"safetensors",
"qwen2",
"pretrained",
"text-generation",
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"license:other",
"region:us"
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"en"
] | TAGS
#mlx #safetensors #qwen2 #pretrained #text-generation #conversational #en #license-other #region-us
|
# mlx-community/Qwen1.5-72B-4bit
This model was converted to MLX format from ['Qwen/Qwen1.5-72B']() using mlx-lm version 0.9.0.
Refer to the original model card for more details on the model.
## Use with mlx
| [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | domenicrosati/adversarial_loss_lr_1e-5_attack_meta-llama_Llama-2-7b-chat-hf_4_3e-5_1k | null | [
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# Model Card for Model ID
## Model Details
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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automatic-speech-recognition | transformers |
<!-- 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. -->
# Whisper Small Ar - H Shams
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-sm... | {"language": ["ar"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_11_0"], "metrics": ["wer"], "base_model": "openai/whisper-small", "model-index": [{"name": "Whisper Small Ar - H Shams", "results": [{"task": {"type": "automatic-speech-recognition", "name": "... | HarithKharrufa/whisper-small-ar | null | [
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| Whisper Small Ar - H Shams
==========================
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3402
* Wer: 45.0739
Model description
-----------------
More information needed
Intended uses & ... | [
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text-classification | transformers |
<!-- 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. -->
# distilbert-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncase... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "distilbert-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "emotion", "typ... | aliciiavs/distilbert-emotion | null | [
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| distilbert-emotion
==================
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1371
* Accuracy: 0.939
Model description
-----------------
More information needed
Intended uses & limitations
--------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
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text-to-image | diffusers | # Mamimi_Samejima_Pony_SDXL
<Gallery />
## Trigger words
You should use `Mamimi_Samejima` to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Download](/kkleskk/Mamimi_Samejima_Pony_SDXL/tree/main) them in the Files & versions tab.
| {"tags": ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora"], "widget": [{"text": "-", "output": {"url": "images/ComfyUI_03333_.png"}}], "base_model": "stablediffusionapi/pony-diffusion-v6-xl", "instance_prompt": "Mamimi_Samejima"} | kkleskk/Mamimi_Samejima_Pony_SDXL | null | [
"diffusers",
"text-to-image",
"stable-diffusion",
"lora",
"template:sd-lora",
"base_model:stablediffusionapi/pony-diffusion-v6-xl",
"region:us"
] | null | 2024-04-13T19:43:36+00:00 | [] | [] | TAGS
#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-stablediffusionapi/pony-diffusion-v6-xl #region-us
| # Mamimi_Samejima_Pony_SDXL
<Gallery />
## Trigger words
You should use 'Mamimi_Samejima' to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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null | peft |
<!-- 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. -->
# icellama_domar_finetune
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama... | {"library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-hf", "model-index": [{"name": "icellama_domar_finetune", "results": []}]} | thorirhrafn/icellama_domar_finetune | null | [
"peft",
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"safetensors",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-hf",
"region:us"
] | null | 2024-04-13T19:46:06+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #generated_from_trainer #base_model-meta-llama/Llama-2-7b-hf #region-us
| icellama\_domar\_finetune
=========================
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9310
Model description
-----------------
More information needed
Intended uses & limitations
------------... | [
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null | null | **Original:** https://huggingface.co/victunes/TherapyBeagle-11B-v2
# TherapyBeagle 11B v2
_Buddy is here for {{user}}._
Trained on top of [vicgalle/CarbonBeagle-11B-truthy](https://huggingface.co/v... | {"license": "cc-by-nc-4.0", "datasets": ["victunes/nart-100k-synthetic-buddy-mixed-names"]} | victunes/TherapyBeagle-11B-v2-GGUF | null | [
"gguf",
"dataset:victunes/nart-100k-synthetic-buddy-mixed-names",
"license:cc-by-nc-4.0",
"region:us"
] | null | 2024-04-13T19:48:56+00:00 | [] | [] | TAGS
#gguf #dataset-victunes/nart-100k-synthetic-buddy-mixed-names #license-cc-by-nc-4.0 #region-us
| Original: URL
# TherapyBeagle 11B v2
_Buddy is here for {{user}}._
!image/png
Trained on top of vicgalle/CarbonBeagle-11B-truthy using a modified version of jerryjalapeno/nart-100k-synthetic.
TherapyBeagle is _hopefully_ aligned to be helpful, healthy, and comforting.
## Usage
- Do not hold back on TherapyBeagle... | [
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text-to-image | diffusers |
# AutoTrain SDXL LoRA DreamBooth - rfhuang/maui-large
<Gallery />
## Model description
These are rfhuang/maui-large LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using [DreamBooth](https://dreambooth.github.io/).
LoRA for the text encoder was enabled: False.
Sp... | {"license": "openrail++", "tags": ["autotrain", "stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "lora", "template:sd-lora"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "A photo of a dog named Maui in random situations, taken from a smartphone camer... | rfhuang/maui-large | null | [
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"lora",
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"license:openrail++",
"region:us"
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|
# AutoTrain SDXL LoRA DreamBooth - rfhuang/maui-large
<Gallery />
## Model description
These are rfhuang/maui-large LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using DreamBooth.
LoRA for the text encoder was enabled: False.
Special VAE used for training: None... | [
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** ... | {"library_name": "peft", "base_model": "google/long-t5-tglobal-base"} | dsolomon/long-t5-global-pubmed-LoRA-r4-i512-o128 | null | [
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"base_model:google/long-t5-tglobal-base",
"region:us"
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"1910.09700"
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#peft #safetensors #arxiv-1910.09700 #base_model-google/long-t5-tglobal-base #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
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- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
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text-generation | transformers |
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_pat... | {"license": "other", "library_name": "transformers", "tags": ["autotrain", "text-generation-inference", "text-generation", "peft"], "widget": [{"messages": [{"role": "user", "content": "What is your favorite condiment?"}]}]} | shaswatamitra/zephyr-7b-beta-finetuned1 | null | [
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#transformers #safetensors #autotrain #text-generation-inference #text-generation #peft #conversational #license-other #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
# Usage
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text-generation | transformers |
Quantized GGUF models from [Vezora/Mistral-22B-v0.2](https://huggingface.co/Vezora/Mistral-22B-v0.2)
### Original Mistral-22b-v.02 Model Card
<img src="https://huggingface.co/Vezora/Mistral-22B-v0.1/resolve/main/unsloth.png" width="100" height="150" />
### Mistral-22b-v.02 Release Announcement 🚀
## This model is ... | {"license": "apache-2.0"} | failspy/Mistral-22B-v0.2-GGUF | null | [
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#transformers #gguf #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
Quantized GGUF models from Vezora/Mistral-22B-v0.2
### Original Mistral-22b-v.02 Model Card
<img src="URL width="100" height="150" />
### Mistral-22b-v.02 Release Announcement
## This model is not an moe, it is infact a 22B parameter dense model!
Date: April 13
Creator Nicolas Mejia-Petit
### Overview
- Just tw... | [
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null | adapter-transformers |
# Adapter `BigTMiami/BB_seq_bn_P_3_seq_bn_C_20` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_helpfulness](https://huggingface.co/datasets/BigTMiami/amazon_helpfulness/) dataset and includes a prediction head for classification.
This adapt... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_helpfulness"]} | BigTMiami/BB_seq_bn_P_3_seq_bn_C_20 | null | [
"adapter-transformers",
"roberta",
"dataset:BigTMiami/amazon_helpfulness",
"region:us"
] | null | 2024-04-13T19:54:36+00:00 | [] | [] | TAGS
#adapter-transformers #roberta #dataset-BigTMiami/amazon_helpfulness #region-us
|
# Adapter 'BigTMiami/BB_seq_bn_P_3_seq_bn_C_20' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_helpfulness dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters library.
## Usage
First, install 'adapters':
... | [
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null | transformers |
# Uploaded model
- **Developed by:** czaplon
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-instruct-v0.2-bnb-4bit
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/uns... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-instruct-v0.2-bnb-4bit"} | czaplon/new-postQQlong-kromera | null | [
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|
# Uploaded model
- Developed by: czaplon
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-instruct-v0.2-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
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text-generation | transformers | **GGUF:** https://huggingface.co/victunes/TherapyBeagle-11B-v2-GGUF
# TherapyBeagle 11B v2
_Buddy is here for {{user}}._
Trained on top of [vicgalle/CarbonBeagle-11B-truthy](https://huggingface.co/... | {"license": "cc-by-nc-4.0", "datasets": ["victunes/nart-100k-synthetic-buddy-mixed-names"]} | victunes/TherapyBeagle-11B-v2 | null | [
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| GGUF: URL
# TherapyBeagle 11B v2
_Buddy is here for {{user}}._
!image/png
Trained on top of vicgalle/CarbonBeagle-11B-truthy using a modified version of jerryjalapeno/nart-100k-synthetic.
TherapyBeagle is _hopefully_ aligned to be helpful, healthy, and comforting.
## Usage
- Do not hold back on TherapyBeagle.
- ... | [
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reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"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": "LunarL... | lucyc/lunar-lander-model-1 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-13T19:58:48+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
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"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
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] |
question-answering | transformers |
<!-- 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. -->
# roberta-finetuned-ChennaiQA-final
This model is a fine-tuned version of [deepset/roberta-base-squad2](https://huggingface.co/dee... | {"license": "cc-by-4.0", "tags": ["generated_from_trainer"], "base_model": "deepset/roberta-base-squad2", "model-index": [{"name": "roberta-finetuned-ChennaiQA-final", "results": []}]} | aditi2212/roberta-finetuned-ChennaiQA-final | null | [
"transformers",
"safetensors",
"roberta",
"question-answering",
"generated_from_trainer",
"base_model:deepset/roberta-base-squad2",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T20:00:57+00:00 | [] | [] | TAGS
#transformers #safetensors #roberta #question-answering #generated_from_trainer #base_model-deepset/roberta-base-squad2 #license-cc-by-4.0 #endpoints_compatible #region-us
|
# roberta-finetuned-ChennaiQA-final
This model is a fine-tuned version of deepset/roberta-base-squad2 on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Tra... | [
"# roberta-finetuned-ChennaiQA-final\n\nThis model is a fine-tuned version of deepset/roberta-base-squad2 on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## T... | [
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"# roberta-finetuned-ChennaiQA-final\n\nThis model is a fine-tuned version of deepset/roberta-base-squad2 on the None dataset.",
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null | null |
Refer [this](https://celeb-recognition.readthedocs.io/en/main/) for detailed documentation.
You can also read my article on medium [here](https://medium.com/@shobhitgupta/celebrity-recognition-using-vggface-and-annoy-363c5df31f1e).
## Basic working of the algorithm includes the following:
- Face detection is ... | {"license": "mit"} | resnet151/celeb_detector | null | [
"onnx",
"license:mit",
"region:us"
] | null | 2024-04-13T20:01:00+00:00 | [] | [] | TAGS
#onnx #license-mit #region-us
|
Refer this for detailed documentation.
You can also read my article on medium here.
## Basic working of the algorithm includes the following:
- Face detection is done using face_recognition module.
- Face encodings are created using VGGFace model (converted to pytorch here).
- Face matching is done usin... | [
"## Basic working of the algorithm includes the following:\r\n- Face detection is done using face_recognition module.\r\n\r\n- Face encodings are created using VGGFace model (converted to pytorch here).\r\n\r\n- Face matching is done using annoy library.",
"## Installing dependencies\r\n- Run 'pip install -r URL'... | [
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text2text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | falba/t5-base-finetuned-news-ep1 | null | [
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#transformers #safetensors #t5 #text2text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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automatic-speech-recognition | transformers |
<!-- 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. -->
# Whisper Medium - Denis Musinguzi
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/wh... | {"language": ["sw"], "license": "apache-2.0", "tags": ["hf-asr-leaderboard", "generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_14_0"], "metrics": ["wer"], "base_model": "openai/whisper-medium", "model-index": [{"name": "Whisper Medium - Denis Musinguzi", "results": [{"task": {"type": "automatic-... | dmusingu/WHISPER-MEDIUM-SWAHILI-ASR-CV-14 | null | [
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| Whisper Medium - Denis Musinguzi
================================
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 14.0 dataset.
It achieves the following results on the evaluation set:
* Cer: 0.0622
* Loss: 0.2969
* Wer: 0.2355
Model description
-----------------
More information... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
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null | transformers |
<h1 align="center"><font color="red">Fine-Tuning do Gemma-2b com dados de DataScience Q&A</font></h1>
Este modelo é um Fine-tuning do modelo do Google Gemma-2b com dados de DataScience Q&A, para a tarefa de Question-Answer 🤗.
Este treinamento foi baseado no tutorial de [Divyang Mandal](), ademais o Dataset pode se... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["NLP", "Q&A"]} | EddyGiusepe/Gemma-2b-DataScienceQnA | null | [
"transformers",
"safetensors",
"NLP",
"Q&A",
"en",
"license:apache-2.0",
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"en"
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#transformers #safetensors #NLP #Q&A #en #license-apache-2.0 #endpoints_compatible #region-us
|
<h1 align="center"><font color="red">Fine-Tuning do Gemma-2b com dados de DataScience Q&A</font></h1>
Este modelo é um Fine-tuning do modelo do Google Gemma-2b com dados de DataScience Q&A, para a tarefa de Question-Answer .
Este treinamento foi baseado no tutorial de [Divyang Mandal](), ademais o Dataset pode ser ... | [] | [
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** ... | {"library_name": "peft", "base_model": "vilsonrodrigues/falcon-7b-instruct-sharded"} | deepaknh/falcon7B_FineTuning_ReExperiment_1_QLORA_7perParam_ILR_increased_v3 | null | [
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"1910.09700"
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#peft #arxiv-1910.09700 #base_model-vilsonrodrigues/falcon-7b-instruct-sharded #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Funded by [optional]:
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- Finetuned from model [optional]:
### Model Sources [optional]
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | nagayoshi3/gpt_0.125B_global_step400_openassistant | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-to-image | diffusers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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# Model Card for Model ID
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | gkMSDA/Llama-2-7b-FinChatGTP298_DJ30_Model_3v2 | null | [
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# Model Card for Model ID
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text-generation | transformers | # GreenBit LLMs
This is GreenBitAI's pretrained **low-bit** LLMs with extreme compression yet still strong performance.
Please refer to our [Github page](https://github.com/GreenBitAI/green-bit-llm) for the code to run the model and more information.
| {"license": "apache-2.0"} | GreenBitAI/Mistral-7B-Instruct-v0.2-layer-mix-bpw-2.5 | null | [
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"safetensors",
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"text-generation",
"conversational",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-13T20:19:32+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # GreenBit LLMs
This is GreenBitAI's pretrained low-bit LLMs with extreme compression yet still strong performance.
Please refer to our Github page for the code to run the model and more information.
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text-to-image | diffusers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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#diffusers #safetensors #arxiv-1910.09700 #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
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## Model Details
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This is the model card of a diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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text2text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | cranonieu2021/pegasus-on-lectures | null | [
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#transformers #safetensors #pegasus #text2text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #has_space #region-us
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-to-image | diffusers | # MiniDiffusion 1
## Model description
Welcome to MiniDiffusion 1!
My first ever model!
Try it now!
## Download model
Weights for this model are available in Safetensors format.
[Download](/GamerC0der/MiniDiffusion1/tree/main) them in the Files & versions tab.
## Use Via Code!!!
```python
import requests
API_U... | {"license": "unknown", "tags": ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora"], "widget": [{"text": "Dog, Realistic, 4k, 8k"}], "base_model": "runwayml/stable-diffusion-v1-5"} | GamerC0der/MiniDiffusion1 | null | [
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#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-runwayml/stable-diffusion-v1-5 #license-unknown #region-us
| # MiniDiffusion 1
## Model description
Welcome to MiniDiffusion 1!
My first ever model!
Try it now!
## Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
## Use Via Code!!!
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null | mlx |
# GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-2.5-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-2.5`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-2.5) for more details on the model.
## Use with m... | {"license": "apache-2.0", "tags": ["mlx"]} | GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-2.5-mlx | null | [
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"safetensors",
"qwen2",
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#mlx #safetensors #qwen2 #license-apache-2.0 #region-us
|
# GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-2.5-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-2.5']().
Refer to the original model card for more details on the model.
## Use with mlx
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null | mlx |
# GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-3.0-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-3.0`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-3.0) for more details on the model.
## Use with m... | {"license": "apache-2.0", "tags": ["mlx"]} | GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-3.0-mlx | null | [
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#mlx #safetensors #qwen2 #license-apache-2.0 #region-us
|
# GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-3.0-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-3.0']().
Refer to the original model card for more details on the model.
## Use with mlx
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null | mlx |
# GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-2.2-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-2.2`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-2.2) for more details on the model.
## Use with m... | {"license": "apache-2.0", "tags": ["mlx"]} | GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-2.2-mlx | null | [
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#mlx #safetensors #qwen2 #license-apache-2.0 #region-us
|
# GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-2.2-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-2.2']().
Refer to the original model card for more details on the model.
## Use with mlx
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null | peft |
<!-- 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. -->
# mistral-hf-platypus-lamini-vxxiii-chat
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "mistral-hf-platypus-lamini-vxxiii-chat", "results": []}]} | NassimB/mistral-hf-platypus-lamini-vxxiii-chat | null | [
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|
# mistral-hf-platypus-lamini-vxxiii-chat
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
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automatic-speech-recognition | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | SpideyDLK/wav2vec2-large-xls-r-300m-sinhala-original-split-part1 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers | # merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* [arcee-ai/sec-mistral-7b-instruct-1.6-epoch]... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["arcee-ai/sec-mistral-7b-instruct-1.6-epoch", "cognitivecomputations/dolphin-2.8-mistral-7b-v02"]} | mergekit-community/mergekit-slerp-dafvhck | null | [
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"text-generation-inference... | null | 2024-04-13T20:42:55+00:00 | [] | [] | TAGS
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| # merge
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* arcee-ai/sec-mistral-7b-instruct-1.6-epoch
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text-classification | transformers |
<!-- 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. -->
# fifi_classification
## First load: April 13, 2024
## University of Oklahoma
The city of Seattle uses a app called FindIt-FixIt ... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["mjbeattie/finditfixit"], "metrics": ["accuracy"], "base_model": "distilbert/distilbert-base-uncased", "model-index": [{"name": "fifi_classification", "results": []}]} | mjbeattie/fifi_classification | null | [
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"region:us"
] | null | 2024-04-13T20:43:48+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #distilbert #text-classification #generated_from_trainer #dataset-mjbeattie/finditfixit #base_model-distilbert/distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| fifi\_classification
====================
First load: April 13, 2024
--------------------------
University of Oklahoma
----------------------
The city of Seattle uses a app called FindIt-FixIt to gather service requests from residents. The requests routed to the responsible agency for resolution. In 2023, we obta... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 4",
"### Traini... | [
"TAGS\n#transformers #tensorboard #safetensors #distilbert #text-classification #generated_from_trainer #dataset-mjbeattie/finditfixit #base_model-distilbert/distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyp... | [
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image-text-to-text | transformers | # ADD HEAD
```
print('Add Vision...')
# ADD HEAD
# Combine pre-trained encoder and pre-trained decoder to form a Seq2Seq model
Vmodel = VisionEncoderDecoderModel.from_encoder_decoder_pretrained(
"google/vit-base-patch16-224-in21k", "LeroyDyer/Mixtral_AI_Tiny"
)
_Encoder_ImageProcessor = Vmodel.encoder
_Decod... | {"language": ["en"], "library_name": "transformers", "tags": ["vision"], "pipeline_tag": "image-text-to-text"} | LeroyDyer/Mixtral_AI_MiniTronVision | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"vision",
"image-text-to-text",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-13T20:51:26+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #mistral #text-generation #vision #image-text-to-text #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # ADD HEAD
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"# ADD HEAD"
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] |
null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- quant_method: QuantizationMethod.BITS_AND_BYTES
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: Fals... | {"language": ["en"], "library_name": "peft", "tags": ["QA"], "datasets": ["SalehAhmad/Intiial-Knowledge-And-Detailed-Assessment-JSON-Format-Data"]} | SalehAhmad/Mistral-7B-Instruct-v0.1-JSON-Test_Generation-2-Epoch | null | [
"peft",
"safetensors",
"mistral",
"QA",
"en",
"dataset:SalehAhmad/Intiial-Knowledge-And-Detailed-Assessment-JSON-Format-Data",
"region:us"
] | null | 2024-04-13T20:53:49+00:00 | [] | [
"en"
] | TAGS
#peft #safetensors #mistral #QA #en #dataset-SalehAhmad/Intiial-Knowledge-And-Detailed-Assessment-JSON-Format-Data #region-us
| ## Training procedure
The following 'bitsandbytes' quantization config was used during training:
- quant_method: QuantizationMethod.BITS_AND_BYTES
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: Fals... | [
"## Training procedure\nThe following 'bitsandbytes' quantization config was used during training:\n- quant_method: QuantizationMethod.BITS_AND_BYTES\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16... | [
"TAGS\n#peft #safetensors #mistral #QA #en #dataset-SalehAhmad/Intiial-Knowledge-And-Detailed-Assessment-JSON-Format-Data #region-us \n",
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"TAGS\n#peft #safetensors #mistral #QA #en #dataset-SalehAhmad/Intiial-Knowledge-And-Detailed-Assessment-JSON-Format-Data #region-us \n## Training procedure\nThe following 'bitsandbytes' quantization config was used during training:\n- quant_method: QuantizationMethod.BITS_AND_BYTES\n- load_in_8bit: False\n- load_i... |
automatic-speech-recognition | transformers |
Mistral
SPEECH-ENCODER-DECODER-MODEL
```
works fine just add custom training
print('Add Audio...')
#Add Head
# Combine pre-trained encoder and pre-trained decoder to form a Seq2Seq model
_AudioFeatureExtractor = AutoFeatureExtractor.from_pretrained("openai/whisper-small")
_AudioTokenizer = AutoTokenizer.from_pretra... | {"language": ["en"], "license": "mit", "library_name": "transformers", "pipeline_tag": "automatic-speech-recognition"} | LeroyDyer/Mixtral_AI_TinyTronSpeech | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"automatic-speech-recognition",
"en",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-13T20:55:08+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #mistral #text-generation #automatic-speech-recognition #en #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
Mistral
SPEECH-ENCODER-DECODER-MODEL
| [] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #automatic-speech-recognition #en #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
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] |
image-to-text | transformers |
# ADD HEAD
```
Mistral
VISION-ENCODER-DECODER-MODEL
print('Add Vision...')
# ADD HEAD
# Combine pre-trained encoder and pre-trained decoder to form a Seq2Seq model
Vmodel = VisionEncoderDecoderModel.from_encoder_decoder_pretrained(
"google/vit-base-patch16-224-in21k", "LeroyDyer/Mixtral_AI_Tiny"
)
_Encoder_Im... | {"language": ["en"], "license": "mit", "library_name": "transformers", "tags": ["vision", "VISION-ENCODER-DECODER-MODEL"], "pipeline_tag": "image-to-text"} | LeroyDyer/Mixtral_AI_TinyTronVision | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"vision",
"VISION-ENCODER-DECODER-MODEL",
"image-to-text",
"en",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-13T20:56:00+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #mistral #text-generation #vision #VISION-ENCODER-DECODER-MODEL #image-to-text #en #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# ADD HEAD
| [
"# ADD HEAD"
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #vision #VISION-ENCODER-DECODER-MODEL #image-to-text #en #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# ADD HEAD"
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] |
null | transformers |
# Creation Process
Vmodel = VisionEncoderDecoderModel.from_encoder_decoder_pretrained(
"google/vit-base-patch16-224-in21k", "LeroyDyer/Mixtral_AI_Tiny"
)
_Encoder_ImageProcessor = Vmodel.encoder
_Decoder_ImageTokenizer = Vmodel.decoder
_VisionEncoderDecoderModel = Vmodel
# Add Pad tokems
LM_MODEL.VisionEncoderDe... | {"language": ["en"], "license": "mit", "library_name": "transformers", "tags": ["vision ", "speech", "image-text-text", "audio-text-text", "Multi-Modal"]} | LeroyDyer/Mixtral_AI_MiniModalTron | null | [
"transformers",
"safetensors",
"vision ",
"speech",
"image-text-text",
"audio-text-text",
"Multi-Modal",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T21:01:54+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #vision #speech #image-text-text #audio-text-text #Multi-Modal #en #license-mit #endpoints_compatible #region-us
|
# Creation Process
Vmodel = VisionEncoderDecoderModel.from_encoder_decoder_pretrained(
"google/vit-base-patch16-224-in21k", "LeroyDyer/Mixtral_AI_Tiny"
)
_Encoder_ImageProcessor = Vmodel.encoder
_Decoder_ImageTokenizer = Vmodel.decoder
_VisionEncoderDecoderModel = Vmodel
# Add Pad tokems
LM_MODEL.VisionEncoderDe... | [
"# Creation Process\n\n\nVmodel = VisionEncoderDecoderModel.from_encoder_decoder_pretrained(\n \"google/vit-base-patch16-224-in21k\", \"LeroyDyer/Mixtral_AI_Tiny\"\n)\n_Encoder_ImageProcessor = Vmodel.encoder\n_Decoder_ImageTokenizer = Vmodel.decoder\n_VisionEncoderDecoderModel = Vmodel",
"# Add Pad tokems\nLM... | [
"TAGS\n#transformers #safetensors #vision #speech #image-text-text #audio-text-text #Multi-Modal #en #license-mit #endpoints_compatible #region-us \n",
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | Erfan-Shayegani/opt-1.3b-lora_Unlearned | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T21:02:23+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
"# Model Card for Model ID",
"## Model Details",
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"# Model Card for Model ID",
"## Model Details",
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text-generation | transformers | # merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* [Equall/Saul-Base](https://huggingface.co/Eq... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["Equall/Saul-Base", "HuggingFaceH4/zephyr-7b-beta"]} | mergekit-community/mergekit-slerp-aywerbb | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"mergekit",
"merge",
"conversational",
"base_model:Equall/Saul-Base",
"base_model:HuggingFaceH4/zephyr-7b-beta",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-13T21:05:55+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #mergekit #merge #conversational #base_model-Equall/Saul-Base #base_model-HuggingFaceH4/zephyr-7b-beta #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # merge
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* Equall/Saul-Base
* HuggingFaceH4/zephyr-7b-beta
### Configuration
The following... | [
"# merge\n\nThis is a merge of pre-trained language models created using mergekit.",
"## Merge Details",
"### Merge Method\n\nThis model was merged using the SLERP merge method.",
"### Models Merged\n\nThe following models were included in the merge:\n* Equall/Saul-Base\n* HuggingFaceH4/zephyr-7b-beta",
"##... | [
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null | transformers |
# Uploaded model
- **Developed by:** czaplon
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-instruct-v0.2-bnb-4bit
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/uns... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-instruct-v0.2-bnb-4bit"} | czaplon/s-detector | null | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"mistral",
"trl",
"en",
"base_model:unsloth/mistral-7b-instruct-v0.2-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T21:06:29+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #text-generation-inference #unsloth #mistral #trl #en #base_model-unsloth/mistral-7b-instruct-v0.2-bnb-4bit #license-apache-2.0 #endpoints_compatible #region-us
|
# Uploaded model
- Developed by: czaplon
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-instruct-v0.2-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
"# Uploaded model\n\n- Developed by: czaplon\n- License: apache-2.0\n- Finetuned from model : unsloth/mistral-7b-instruct-v0.2-bnb-4bit\n\nThis mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
"TAGS\n#transformers #safetensors #text-generation-inference #unsloth #mistral #trl #en #base_model-unsloth/mistral-7b-instruct-v0.2-bnb-4bit #license-apache-2.0 #endpoints_compatible #region-us \n",
"# Uploaded model\n\n- Developed by: czaplon\n- License: apache-2.0\n- Finetuned from model : unsloth/mistral-7b-... | [
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automatic-speech-recognition | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | SpideyDLK/wav2vec2-large-xls-r-300m-sinhala-aug-data-with-original-split-part1 | null | [
"transformers",
"tensorboard",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T21:06:59+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #tensorboard #safetensors #wav2vec2 #automatic-speech-recognition #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s)... | [
"TAGS\n#transformers #tensorboard #safetensors #wav2vec2 #automatic-speech-recognition #arxiv-1910.09700 #endpoints_compatible #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This mo... | [
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null | transformers |
<!-- 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. -->
# videomae-base-ftuned-tomo1-try1
This model was trained from scratch on an unknown dataset.
It achieves the following results on ... | {"tags": ["generated_from_trainer"], "model-index": [{"name": "videomae-base-ftuned-tomo1-try1", "results": []}]} | harttj/videomae-base-ftuned-tomo1-try1 | null | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T21:07:31+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #generated_from_trainer #endpoints_compatible #region-us
|
# videomae-base-ftuned-tomo1-try1
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.3627
- eval_accuracy: 0.8104
- eval_runtime: 638.9322
- eval_samples_per_second: 2.567
- eval_steps_per_second: 0.642
- step: 0
## Model description
... | [
"# videomae-base-ftuned-tomo1-try1\n\nThis model was trained from scratch on an unknown dataset.\nIt achieves the following results on the evaluation set:\n- eval_loss: 0.3627\n- eval_accuracy: 0.8104\n- eval_runtime: 638.9322\n- eval_samples_per_second: 2.567\n- eval_steps_per_second: 0.642\n- step: 0",
"## Mode... | [
"TAGS\n#transformers #tensorboard #safetensors #generated_from_trainer #endpoints_compatible #region-us \n",
"# videomae-base-ftuned-tomo1-try1\n\nThis model was trained from scratch on an unknown dataset.\nIt achieves the following results on the evaluation set:\n- eval_loss: 0.3627\n- eval_accuracy: 0.8104\n- e... | [
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="mxmilian/q-Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.22 +/... | mxmilian/q-Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-13T21:12:54+00:00 | [] | [] | TAGS
#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
## Usage
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] |
text-to-image | null |
# LoRA model of Necron Misha/ミーシャ・ネクロン (Maou Gakuin no Futekigousha)
## What Is This?
This is the LoRA model of waifu Necron Misha/ミーシャ・ネクロン (Maou Gakuin no Futekigousha).
## How Is It Trained?
* This model is trained with [kohya-ss/sd-scripts](https://github.com/kohya-ss/sd-scripts), and the test images are gener... | {"license": "mit", "tags": ["art", "not-for-all-audiences"], "datasets": ["CyberHarem/necron_misha_maougakuinnofutekigousha", "BangumiBase/maougakuinnofutekigousha"], "pipeline_tag": "text-to-image"} | CyberHarem/necron_misha_maougakuinnofutekigousha | null | [
"art",
"not-for-all-audiences",
"text-to-image",
"dataset:CyberHarem/necron_misha_maougakuinnofutekigousha",
"dataset:BangumiBase/maougakuinnofutekigousha",
"license:mit",
"region:us"
] | null | 2024-04-13T21:14:55+00:00 | [] | [] | TAGS
#art #not-for-all-audiences #text-to-image #dataset-CyberHarem/necron_misha_maougakuinnofutekigousha #dataset-BangumiBase/maougakuinnofutekigousha #license-mit #region-us
| LoRA model of Necron Misha/ミーシャ・ネクロン (Maou Gakuin no Futekigousha)
==================================================================
What Is This?
-------------
This is the LoRA model of waifu Necron Misha/ミーシャ・ネクロン (Maou Gakuin no Futekigousha).
How Is It Trained?
------------------
* This model is trained wi... | [] | [
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] | [
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"TAGS\n#art #not-for-all-audiences #text-to-image #dataset-CyberHarem/necron_misha_maougakuinnofutekigousha #dataset-BangumiBase/maougakuinnofutekigousha #license-mit #region-us \n"
] |
text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | shallow6414/5b8v6hr | null | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T21:16:04+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #stablelm #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-classification | transformers |
<!-- 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. -->
# google-t5-small
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unkn... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall"], "base_model": "google-t5/t5-small", "model-index": [{"name": "google-t5-small", "results": []}]} | xshubhamx/google-t5-small | null | [
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"base_model:google-t5/t5-small",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
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| google-t5-small
===============
This model is a fine-tuned version of google-t5/t5-small on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9027
* Accuracy: 0.7963
* Precision: 0.7873
* Recall: 0.7963
* Precision Macro: 0.7130
* Recall Macro: 0.7178
* Macro Fpr: 0.0186
* Weigh... | [
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text-generation | transformers |
### Overview
Another experimental model, using mostly sythetic data generated by [airoboros](https://github.com/jondurbin/airoboros)
This fine-tune is on the updated yi-34b-200k, which is supposedly much better at longer contexts.
#### Highlights
This is using yi-34b-200k as the base model. While the base model s... | {"license": "other", "datasets": ["jondurbin/airoboros-3.2", "bluemoon-fandom-1-1-rp-cleaned", "boolq", "jondurbin/gutenberg-dpo-v0.1", "LDJnr/Capybara", "jondurbin/cinematika-v0.1", "glaiveai/glaive-function-calling-v2", "grimulkan/LimaRP-augmented", "piqa", "Vezora/Tested-22k-Python-Alpaca", "mattpscott/airoboros-sum... | blockblockblock/airoboros-34b-3.3-bpw2.25 | null | [
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"dataset:LDJnr/Capybara",
"dataset:jondurbin/cinematika-v0.1",
"dataset:glaiveai/glaive-function-callin... | null | 2024-04-13T21:20:34+00:00 | [] | [] | TAGS
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### Overview
Another experimental model, using mostly sythetic data generated by airoboros
This fine-tune is on the updated yi-34b-200k, which is supposedly much better at longer contexts.
#### Highlights
This is using yi-34b-200k as the base model. While the base model supports 200k context size, this model was ... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | cackerman/rewrites_llama13bchat_4bit_ft_full | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
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"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Shared by [optional]:
- Model type:
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token-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | gtang11/task2 | null | [
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"gpt2",
"token-classification",
"arxiv:1910.09700",
"autotrain_compatible",
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"region:us"
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | cindy990915/duke_chatbot_0413 | null | [
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#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
slightly more tuned [and still pretty useless] version of lobollama.
# Uploaded model
- **Developed by:** reallad
- **License:** apache-2.0
- **Finetuned from model :** reallad/lesslobollama
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl", "sft"], "base_model": "reallad/lesslobollama"} | reallad/lesslobollama2 | null | [
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|
slightly more tuned [and still pretty useless] version of lobollama.
# Uploaded model
- Developed by: reallad
- License: apache-2.0
- Finetuned from model : reallad/lesslobollama
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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null | peft |
<!-- 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. -->
# Mistral-7B-Instruct-v0.2-finetuned-justification-v01
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "Mistral-7B-Instruct-v0.2-finetuned-justification-v01", "results": []}]} | satyanshu404/Mistral-7B-Instruct-v0.2-finetuned-justification-v01 | null | [
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#peft #safetensors #trl #sft #generated_from_trainer #base_model-mistralai/Mistral-7B-Instruct-v0.2 #license-apache-2.0 #region-us
| Mistral-7B-Instruct-v0.2-finetuned-justification-v01
====================================================
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 2.7757
Model description
-----------------
More... | [
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52
] | [
"TAGS\n#peft #safetensors #trl #sft #generated_from_trainer #base_model-mistralai/Mistral-7B-Instruct-v0.2 #license-apache-2.0 #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 4\n... |
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