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text-generation | transformers |  | {"language": ["sv", "da", "no", "is", "en"], "license": "apache-2.0", "pipeline_tag": "text-generation", "base_model": ["upstage/SOLAR-10.7B-v1.0"]} | timpal0l/sol | null | [
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text-generation | transformers |
# Experimenting-Test4.5-8B-2
Experimenting-Test4.5-8B-2 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Kaoeiri/Experimenting-Test3.5-8B-2](https://huggingface.co/Kaoeiri/Experimenting-Test3.5-8B-2)
* [cgato/L3-TheSpice... | {"tags": ["merge", "mergekit", "lazymergekit", "Kaoeiri/Experimenting-Test3.5-8B-2", "cgato/L3-TheSpice-8b-v0.1.3", "Sao10K/L3-Solana-8B-v1"], "base_model": ["Kaoeiri/Experimenting-Test3.5-8B-2", "cgato/L3-TheSpice-8b-v0.1.3", "Sao10K/L3-Solana-8B-v1"]} | Kaoeiri/Experimenting-Test4.5-8B-2 | null | [
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# Experimenting-Test4.5-8B-2
Experimenting-Test4.5-8B-2 is a merge of the following models using LazyMergekit:
* Kaoeiri/Experimenting-Test3.5-8B-2
* cgato/L3-TheSpice-8b-v0.1.3
* Sao10K/L3-Solana-8B-v1
## Configuration
## Usage
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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. -->
# my_awesome_model
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased)... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "my_awesome_model", "results": []}]} | kathleenkatchis/my_awesome_model | null | [
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| my\_awesome\_model
==================
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3421
* Accuracy: 0.8603
Model description
-----------------
More information needed
Intended uses & limitations
--------... | [
"### 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: 2",
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/zuzuka17/LaZardy3_7.3B
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a... | {"language": ["en"], "library_name": "transformers", "base_model": "zuzuka17/LaZardy3_7.3B", "quantized_by": "mradermacher"} | mradermacher/LaZardy3_7.3B-GGUF | null | [
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| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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image-classification | transformers |
# Ocsai-D Web
This model is a trained model for scoring creativity - specifically figural (drawing-based) originality scoring. It is a fine-tuned version of [beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224-pt22k-ft22k).
It achieves the following results on the evaluation set:
- Loss: 0... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["pearsonr", "r_squared"], "base_model": "microsoft/beit-large-patch16-224-pt22k-ft22k", "model-index": [{"name": "motes_mtci_microsoft-beit-large-patch16-224-pt22k-ft22k", "results": []}]} | POrg/ocsai-d-web | null | [
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| Ocsai-D Web
===========
This model is a trained model for scoring creativity - specifically figural (drawing-based) originality scoring. It is a fine-tuned version of beit-large-patch16-224.
It achieves the following results on the evaluation set:
* Loss: 0.0055
* Mse: 0.0055
* Pearsonr: 0.8745
* R2: 0.7224
* Rmse:... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 20\n* eval\\_batch\\_size: 20\n* seed: 42\n* gradient\\_accumulation\\_steps: 8\n* total\\_train\\_batch\\_size: 160\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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null | null | # RoBERTa
Spam messages frequently carry malicious links or phishing attempts posing significant threats to both organizations and their users. By choosing our RoBERTa-based spam message detection system, organizations can greatly enhance their security infrastructure. Our system effectively detects and filters out spa... | {} | anthonysandesh/smishing | null | [
"arxiv:1907.11692",
"region:us"
] | null | 2024-04-24T20:57:36+00:00 | [
"1907.11692"
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#arxiv-1907.11692 #region-us
| RoBERTa
=======
Spam messages frequently carry malicious links or phishing attempts posing significant threats to both organizations and their users. By choosing our RoBERTa-based spam message detection system, organizations can greatly enhance their security infrastructure. Our system effectively detects and filters... | [
"### Dataset Class Distribution\n\n\n\nModel Architecture\n------------------\n\n\nThe model is fine tuned RoBERTa base\n\n\nroberta-base: URL\n\n\npaper: URL\n\n\nMetrics\n-------\n\n\n\nRequired Packages\n-----------------\n\n\n* numpy\n* torch\n* transformers\n* pandas\n* tqdm\n* matplotlib",
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text-generation | transformers |
<img src="./llama-3-merges.webp" alt="Llama-3 DPO Logo" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# Llama-3-70B-Instruct-32k-v0.1
This is an experiment by setting `rope_theta` to `8m`.
# Quantized models
You can find all GGUF quantized models here: [MaziyarPanahi/Llama-3-70B-In... | {"language": ["en"], "license": "other", "library_name": "transformers", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3"], "model_name": "Llama-3-8B-Instruct-32k-v0.1", "base_model": "meta-llama/Meta-Llama-3-70B-Instruct", "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE"... | MaziyarPanahi/Llama-3-70B-Instruct-32k-v0.1 | null | [
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|
<img src="./URL" alt="Llama-3 DPO Logo" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# Llama-3-70B-Instruct-32k-v0.1
This is an experiment by setting 'rope_theta' to '8m'.
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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 Cantanese
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small... | {"language": ["yue"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_16_0"], "metrics": ["wer"], "base_model": "openai/whisper-small", "model-index": [{"name": "Whisper Small Cantanese", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Au... | poppysmickarlili/whisper-small-cantonese_24-04-2024-2043 | null | [
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| Whisper Small Cantanese
=======================
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.0 dataset.
It achieves the following results on the evaluation set:
* Loss: 154.2482
* Wer: 100.0
Model description
-----------------
More information needed
Intended uses & limita... | [
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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]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned-adapters_Aleatoric_tiny_0.4_Seed104 | null | [
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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]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned_Aleatoric_tiny_0.4_Seed104 | null | [
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### Model Description
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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": []} | nospotfer/mistralai-Code-Instruct-Finetune-megamonster | null | [
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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": []} | happylayers/sc13 | null | [
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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": []} | SquareNeo/test_model_trained | null | [
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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_train_seq_cls_run2
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mi... | {"library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "mistral_train_seq_cls_run2", "results": []}]} | isaaclee/mistral_train_seq_cls_run2 | null | [
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|
# mistral_train_seq_cls_run2
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyp... | [
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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": []} | cilantro9246/le6l0kb | 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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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. -->
# outputs
This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/deberta-v3-small", "model-index": [{"name": "outputs", "results": []}]} | vempaliakhil/outputs | null | [
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| outputs
=======
This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1589
* Accuracy: 0.7087
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
... | [
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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": ["trl", "sft"]} | heejincs/mistral-7b-qlora-alpaca-sample-0.5k | 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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reinforcement-learning | ml-agents |
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos**
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-Docum... | {"library_name": "ml-agents", "tags": ["SoccerTwos", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SoccerTwos"]} | jeliasherrero/poca-SoccerTwos | null | [
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"SoccerTwos",
"deep-reinforcement-learning",
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#ml-agents #tensorboard #onnx #SoccerTwos #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SoccerTwos #region-us
|
# poca Agent playing SoccerTwos
This is a trained model of a poca agent playing SoccerTwos
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* ... | [
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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. -->
# my-dear-watson-nli-model
This model is a fine-tuned version of [MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7](https... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7", "model-index": [{"name": "my-dear-watson-nli-model", "results": []}]} | vempaliakhil/my-dear-watson-nli-model | null | [
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"license:mit",
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] | null | 2024-04-24T21:14:37+00:00 | [] | [] | TAGS
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| my-dear-watson-nli-model
========================
This model is a fine-tuned version of MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1099
* Accuracy: 0.8309
Model description
-----------------
More information 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": []} | rPucs/gemma-2b-relextract-NoIt-webnlg | 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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null | null |
# IDLS24 TEAM33
## SKA-TDNN with 3 fcwSKA blocks
Results on Vox1-O, after training on VoxCeleb1-dev
| EER (%) | minDCF|
|---------|-------|
|2.297| 0.16635 | | {"license": "apache-2.0"} | alexgichamba/idls24_team33_vox1_3fcwska | null | [
"license:apache-2.0",
"region:us"
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#license-apache-2.0 #region-us
| IDLS24 TEAM33
=============
SKA-TDNN with 3 fcwSKA blocks
-----------------------------
Results on Vox1-O, after training on VoxCeleb1-dev
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null | null | EXL2 quants of [Phi-3 mini 128k instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct)
[~~2.50 bits per weight~~](https://huggingface.co/turboderp/Phi-3-mini-128k-instruct-exl2/tree/2.5bpw) (broken)
[3.00 bits per weight](https://huggingface.co/turboderp/Phi-3-mini-128k-instruct-exl2/tree/3.0bpw) ... | {} | turboderp/Phi-3-mini-128k-instruct-exl2 | null | [
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#region-us
| EXL2 quants of Phi-3 mini 128k instruct
~~2.50 bits per weight~~ (broken)
3.00 bits per weight
4.00 bits per weight
5.00 bits per weight
6.00 bits per weight
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text-generation | transformers | I'm an innovative concept, created through a cutting-edge training method. Picture me as a "learning bot" who's had a special upgrade. Just like how a chef perfects their recipes with new techniques, my creators have fine-tuned my "knowledge-absorption" process. I'm here to showcase the potential of this new approach, ... | {"language": ["en"], "license": "apache-2.0"} | chrischain/SatoshiNv117 | null | [
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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": []} | whizzzzkid/nose_gemma_ft9 | 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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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. -->
# 0.01_ablation_5iters_bs256_nodpo_iter_5
This model is a fine-tuned version of [ShenaoZ/0.01_ablation_5iters_bs256_nodpo_iter_4](... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "ShenaoZ/0.01_ablation_5iters_bs256_nodpo_iter_4", "model-index": [{"name": "0.01_ablation_5iters_bs256_nodpo_iter_5", "results": []}]} | ShenaoZ/0.01_ablation_5iters_bs256_nodpo_iter_5 | null | [
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|
# 0.01_ablation_5iters_bs256_nodpo_iter_5
This model is a fine-tuned version of ShenaoZ/0.01_ablation_5iters_bs256_nodpo_iter_4 on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More inf... | [
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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. -->
# 0.0_ablation_4iters_bs128_nodpo_iter_1
This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://hugging... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "HuggingFaceH4/mistral-7b-sft-beta", "model-index": [{"name": "0.0_ablation_4iters_bs128_nodpo_iter_1", "results": []}]} | ShenaoZhang/0.0_ablation_4iters_bs128_nodpo_iter_1 | null | [
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# 0.0_ablation_4iters_bs128_nodpo_iter_1
This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed... | [
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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. -->
# 0.01_ablation_4iters_bs128_nodpo_iter_1
This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggin... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "HuggingFaceH4/mistral-7b-sft-beta", "model-index": [{"name": "0.01_ablation_4iters_bs128_nodpo_iter_1", "results": []}]} | ShenaoZhang/0.01_ablation_4iters_bs128_nodpo_iter_1 | null | [
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# 0.01_ablation_4iters_bs128_nodpo_iter_1
This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information neede... | [
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text-to-image | diffusers | # BetterJourneys
<Gallery />
## Model description
Journeys image model for BetterUp
## Trigger words
You should use `In the style of BetterUp` to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Download](/jason-betterup/betterjourneys-sdxl/tree/main... | {"license": "apache-2.0", "tags": ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora"], "widget": [{"text": "In the style of BetterUp, a captain sailing the ocean on a ship with a lighthouse in the background, with a vibrant, high contrast color palette, use rubine colors as a highlight", "out... | jason-betterup/betterjourneys-sdxl | null | [
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#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-apache-2.0 #region-us
| # BetterJourneys
<Gallery />
## Model description
Journeys image model for BetterUp
## Trigger words
You should use 'In the style of BetterUp' 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 |
# 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": "microsoft/Phi-3-mini-128k-instruct"} | Viag/phi-3-triplets-with-description | null | [
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### Model Sources [optional]
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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. -->
# finetuned__beto-clinical-wl-es__augmented-ultrasounds-ner
This model is a fine-tuned version of [manucos/finetuned__beto-clinica... | {"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "manucos/finetuned__beto-clinical-wl-es__augmented-ultrasounds", "model-index": [{"name": "finetuned__beto-clinical-wl-es__augmented-ultrasounds-ner", "results": []}]} | manucos/finetuned__beto-clinical-wl-es__augmented-ultrasounds-ner | null | [
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| finetuned\_\_beto-clinical-wl-es\_\_augmented-ultrasounds-ner
=============================================================
This model is a fine-tuned version of manucos/finetuned\_\_beto-clinical-wl-es\_\_augmented-ultrasounds on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.... | [
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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": []} | CMU-AIR2/math-deepseek-FULL-ArithHard-30k-FTMWP-FULL | null | [
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# Model Card for Model ID
## Model Details
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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. -->
# donut-ft-cordv2-gestai
This model is a fine-tuned version of [naver-clova-ix/donut-base-finetuned-cord-v2](https://huggingface.c... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "naver-clova-ix/donut-base-finetuned-cord-v2", "model-index": [{"name": "donut-ft-cordv2-gestai", "results": []}]} | maikelcm/donut-ft-cordv2-gestai | null | [
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|
# donut-ft-cordv2-gestai
This model is a fine-tuned version of naver-clova-ix/donut-base-finetuned-cord-v2 on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
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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": "deepseek-ai/deepseek-coder-1.3b-instruct"} | CMU-AIR2/math-deepseek-LORA-ArithHardC12-FTMWP-LORA | null | [
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text-generation | null | # Home 1B v3
The "Home" model is a fine tuning of the [TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) model. The model is able to control devices in the user's house via a Home Assistant integragion. The fine tuning dataset a [custom curated dataset](https://github.com/acon96/hom... | {"language": ["en"], "license": "apache-2.0", "tags": ["automation", "home", "assistant"], "datasets": ["acon96/Home-Assistant-Requests"], "pipeline_tag": "text-generation"} | acon96/Home-1B-v3-GGUF | null | [
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text-to-image | diffusers | # KeianiXL
<Gallery />
## Model description
Do not use this for any NSFW purposes.
Do not post this online such as social media platforms.
## Trigger words
You should use `Keiani` to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Download](/ORILIN0... | {"tags": ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora"], "widget": [{"text": "-", "output": {"url": "images/8d2991c5-fbe4-4973-970f-16f08fb7a5b2.png"}}, {"text": "-", "output": {"url": "images/98848e4b-e7b5-4a3b-a8b5-c11432441995.png"}}], "base_model": "stabilityai/stable-diffusion-xl-ba... | ORILIN024/KeianiXL | null | [
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#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-stabilityai/stable-diffusion-xl-base-1.0 #region-us
| # KeianiXL
<Gallery />
## Model description
Do not use this for any NSFW purposes.
Do not post this online such as social media platforms.
## Trigger words
You should use 'Keiani' to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
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feature-extraction | 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": []} | stvhuang/rcr-run-5pqr6lwp-90396-master-0_20240402T105012-ep32 | null | [
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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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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?"}]}]} | cr0afm/autotrain-po8kz-28ik9 | null | [
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# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
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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. -->
# vit-base-beans
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "vit-base-beans", "results": []}]} | miricalderonr/vit-base-beans | null | [
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# vit-base-beans
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset.
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More information needed
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More information needed
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
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### Model Description
<!-- Provide a longer summary of what this model is. -->
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
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### Model Description
<!-- Provide a longer summary of what this model is. -->
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text-generation | transformers |
# Uploaded model
- **Developed by:** Obyz
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-Instruct-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/uns... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-Instruct-bnb-4bit"} | Obyz/Llama3-V1-16bit | null | [
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|
# Uploaded model
- Developed by: Obyz
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-Instruct-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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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": []} | nowave/phi-3-mini-4k-loudai | 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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- Funded by [optional]:
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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. -->
# llama3-8b-sft-qlora-re
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta... | {"license": "other", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "meta-llama/Meta-Llama-3-8B", "model-index": [{"name": "llama3-8b-sft-qlora-re", "results": []}]} | solanaO/llama3-8b-sft-qlora-re | null | [
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|
# llama3-8b-sft-qlora-re
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperp... | [
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"## Intended uses & limitations\n\nMore information needed",
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text-generation | transformers |
Trained for 2 epochs on NilanE/ParallelFiction-Ja_En-100k using QLoRA. CPO tune is in-progress.
Input should be 500-1000 tokens long. Make sure to set 'do_sample = False' if using HF transformers for inference, or otherwise set temperature to 0 for deterministic outputs.
## Prompt format
"""Translate this from Japa... | {"language": ["en", "ja"], "license": "apache-2.0", "tags": ["llama"], "datasets": ["NilanE/ParallelFiction-Ja_En-100k"], "base_model": "NilanE/tinyllama-relora-merge"} | NilanE/tinyllama-en_ja-translation-v3 | null | [
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|
Trained for 2 epochs on NilanE/ParallelFiction-Ja_En-100k using QLoRA. CPO tune is in-progress.
Input should be 500-1000 tokens long. Make sure to set 'do_sample = False' if using HF transformers for inference, or otherwise set temperature to 0 for deterministic outputs.
## Prompt format
"""Translate this from Japa... | [
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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": ["trl", "sft"]} | scottsus/mamba-2.8b-instruct-hf | null | [
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#transformers #safetensors #mamba #text-generation #trl #sft #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]:
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text-generation | transformers |
## Model Details
Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source c... | {"language": ["en"], "license": "other", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE", "extra_gated_prompt": "### META LLAMA 3 COMMUNITY LICENSE AGREEMENT\nMeta Llama 3 Version Release Date: April 18, 2024\n\"Agreemen... | chrischain/Satoshi1337-8B | null | [
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| Model Details
-------------
Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available op... | [
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"### Use with 'llama3'\n\n\nPlease, follow the instructions in the repository.\n\n\nTo download Original checkpoints, see the example command below leveraging 'huggingface-cli':\n\n\nFor Hugging Face support, we recommend using t... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/Guilherme34/Samantha-v5-wizardlm2
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do no... | {"language": ["en"], "library_name": "transformers", "tags": [], "base_model": "Guilherme34/Samantha-v5-wizardlm2", "quantized_by": "mradermacher"} | mradermacher/Samantha-v5-wizardlm2-GGUF | null | [
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#transformers #gguf #en #base_model-Guilherme34/Samantha-v5-wizardlm2 #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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reinforcement-learning | ml-agents |
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos**
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-Docum... | {"library_name": "ml-agents", "tags": ["SoccerTwos", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SoccerTwos"]} | BWangila/poca-SoccerTwos | null | [
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"onnx",
"SoccerTwos",
"deep-reinforcement-learning",
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#ml-agents #tensorboard #onnx #SoccerTwos #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SoccerTwos #region-us
|
# poca Agent playing SoccerTwos
This is a trained model of a poca agent playing SoccerTwos
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* ... | [
"# poca Agent playing SoccerTwos\n This is a trained model of a poca agent playing SoccerTwos\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 ... | [
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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": []} | nrshoudi/speech_ocean_hubert | null | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-24T21:50:41+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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null | transformers |
# Uploaded model
- **Developed by:** SubashNeupane
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-Instruct-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unsl... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-Instruct-bnb-4bit"} | SubashNeupane/llama-3-8b-Instruct-bnb-4bit-medicalQA | null | [
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|
# Uploaded model
- Developed by: SubashNeupane
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-Instruct-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
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null | fastai |
# Amazing!
🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([docume... | {"tags": ["fastai"]} | daledem/entregable2 | null | [
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|
# Amazing!
Congratulations on hosting your fastai model on the Hugging Face Hub!
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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. -->
# beit-base-patch16-224-dmae-va-U5-42E
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/beit-base-patch16-224", "model-index": [{"name": "beit-base-patch16-224-dmae-va-U5-42E", "results": []}]} | Augusto777/beit-base-patch16-224-dmae-va-U5-42E | null | [
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| beit-base-patch16-224-dmae-va-U5-42E
====================================
This model is a fine-tuned version of microsoft/beit-base-patch16-224 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5797
* Accuracy: 0.8333
Model description
-----------------
More information n... | [
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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. -->
# outputs
This model is a fine-tuned version of [unsloth/mistral-7b-instruct-v0.2-bnb-4bit](https://huggingface.co/unsloth/mistral... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "unsloth", "generated_from_trainer"], "metrics": ["accuracy", "bleu", "sacrebleu", "rouge"], "base_model": "unsloth/mistral-7b-instruct-v0.2-bnb-4bit", "model-index": [{"name": "outputs", "results": []}]} | vdavidr/mistral-7b-instruct-v0.2-bnb-4bit_Finetuned_usloth_dataset_size_364_epochs_10 | null | [
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| outputs
=======
This model is a fine-tuned version of unsloth/mistral-7b-instruct-v0.2-bnb-4bit on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0314
* Accuracy: 0.021
* Chrf: 0.987
* Bleu: 0.968
* Sacrebleu: 1.0
* Rouge1: 0.977
* Rouge2: 0.956
* Rougel: 0.977
* Rougelsum: 0... | [
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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 En - Test Run
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-s... | {"language": ["en"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "openai/whisper-small", "model-index": [{"name": "Whisper Small En - Test Run", "results": []}]} | debussyman/whisper-small-hi | null | [
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#transformers #tensorboard #safetensors #whisper #automatic-speech-recognition #generated_from_trainer #en #base_model-openai/whisper-small #license-apache-2.0 #endpoints_compatible #region-us
| Whisper Small En - Test Run
===========================
This model is a fine-tuned version of openai/whisper-small on the My Voice Test Run dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0000
* Wer: 0.0
Model description
-----------------
More information needed
Intended uses & li... | [
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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:** [Vashisth Tiwari, Emily Guo, Amanda Li]
- **Funded by [optional]:** [More Information Needed]
- **Shared by ... | {"library_name": "peft", "base_model": "meta-llama/Llama-2-7b-hf"} | vashistht/bonsai-reasoning-adapter_prune_c4_ft_wiki | null | [
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|
# Model Card for Model ID
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null | null |
# Shadowm7expNeuralsynthesis-7B
Shadowm7expNeuralsynthesis-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
## 🧩 Configuration
```yaml
models:
- model: mistralai/Mistral-7B-v0.1
- model: mahiatlinux/ShadowM7EXP-7B
- model: Kukedlc/Neural... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"]} | automerger/Shadowm7expNeuralsynthesis-7B | null | [
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#merge #mergekit #lazymergekit #automerger #license-apache-2.0 #region-us
|
# Shadowm7expNeuralsynthesis-7B
Shadowm7expNeuralsynthesis-7B is an automated merge created by Maxime Labonne using the following configuration.
## Configuration
## Usage
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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. -->
# my_awesome_eli5_clm-model
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the eli5_category dataset... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["eli5_category"], "base_model": "gpt2", "model-index": [{"name": "my_awesome_eli5_clm-model", "results": []}]} | elyssamcmaster/my_awesome_eli5_clm-model | null | [
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| my\_awesome\_eli5\_clm-model
============================
This model is a fine-tuned version of gpt2 on the eli5\_category dataset.
It achieves the following results on the evaluation set:
* Loss: 3.5919
Model description
-----------------
More information needed
Intended uses & limitations
------------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-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: 3.0",
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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.
... | {"library_name": "diffusers"} | rubbrband/experienceSDXLBETA_experiencexlV2BETA | null | [
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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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text-generation | transformers |
# Dolphin 2.9 Llama 3 70b 🐬
Curated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations
Discord: https://discord.gg/8fbBeC7ZGx
<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" w... | {"language": ["en"], "license": "llama3", "datasets": ["cognitivecomputations/Dolphin-2.9", "teknium/OpenHermes-2.5", "m-a-p/CodeFeedback-Filtered-Instruction", "cognitivecomputations/dolphin-coder", "cognitivecomputations/samantha-data", "HuggingFaceH4/ultrachat_200k", "microsoft/orca-math-word-problems-200k", "abacus... | cognitivecomputations/dolphin-2.9-llama3-70b | null | [
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"dataset:cognitivecompu... | null | 2024-04-24T22:08:04+00:00 | [] | [
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# Dolphin 2.9 Llama 3 70b
Curated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations
Discord: URL
<img src="URL width="600" />
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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. -->
# results-Meta-Llama-3-8B-tagllm-lang-1-fixed-embed
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://hug... | {"license": "other", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "meta-llama/Meta-Llama-3-8B", "model-index": [{"name": "results-Meta-Llama-3-8B-tagllm-lang-1-fixed-embed", "results": []}]} | AlienKevin/Meta-Llama-3-8B-tagllm-lang-1-fixed-embed | null | [
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#peft #safetensors #trl #sft #generated_from_trainer #base_model-meta-llama/Meta-Llama-3-8B #license-other #region-us
| results-Meta-Llama-3-8B-tagllm-lang-1-fixed-embed
=================================================
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 2.9021
Model description
-----------------
More information n... | [
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text-generation | null | ## 💫 Community Model> Phi-3 mini 4k instruct by Microsoft
*👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)*.
**Model creator:** [Microsoft](https://huggingface.co/microsof... | {"language": ["en"], "license": "mit", "tags": ["nlp", "code"], "license_link": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/LICENSE", "pipeline_tag": "text-generation", "quantized_by": "bartowski", "lm_studio": {"param_count": "4b", "use_case": "chat", "release_date": "23-04-2024", "model_crea... | lmstudio-community/Phi-3-mini-4k-instruct-GGUF | null | [
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#gguf #nlp #code #text-generation #en #arxiv-2404.14219 #license-mit #region-us
| ## Community Model> Phi-3 mini 4k instruct by Microsoft
* LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*.
Model creator: Microsoft<br>
Original model: Phi-3-mini-4k-instruct<br>
GGUF quantization: provided by bartowski based on ... | [
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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. -->
# my_awesome_opus_books_model
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown data... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "base_model": "t5-small", "model-index": [{"name": "my_awesome_opus_books_model", "results": []}]} | Ponyyyy/my_awesome_opus_books_model | null | [
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| my\_awesome\_opus\_books\_model
===============================
This model is a fine-tuned version of t5-small on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.6065
* Bleu: 5.7221
* Gen Len: 17.5758
Model description
-----------------
More information needed
Intended u... | [
"### 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: 2\n* mixed\\_prec... | [
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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. -->
# token-classification-llmlingua2-xlm-roberta-bctn-2308_chunk_10epoch
This model is a fine-tuned version of [FacebookAI/xlm-robert... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "FacebookAI/xlm-roberta-large", "model-index": [{"name": "token-classification-llmlingua2-xlm-roberta-bctn-2308_chunk_10epoch", "results": []}]} | qminh369/token-classification-llmlingua2-xlm-roberta-bctn-2308_chunk_10epoch | null | [
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| token-classification-llmlingua2-xlm-roberta-bctn-2308\_chunk\_10epoch
=====================================================================
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1480
Model descript... | [
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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. -->
# test-finetuned__roberta-base-bne__augmented-ultrasounds-ner
This model is a fine-tuned version of [manucos/finetuned__roberta-ba... | {"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "manucos/finetuned__roberta-base-bne__augmented-ultrasounds", "model-index": [{"name": "test-finetuned__roberta-base-bne__augmented-ultrasounds-ner", "results": []}]} | manucos/test-finetuned__roberta-base-bne__augmented-ultrasounds-ner | null | [
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| test-finetuned\_\_roberta-base-bne\_\_augmented-ultrasounds-ner
===============================================================
This model is a fine-tuned version of manucos/finetuned\_\_roberta-base-bne\_\_augmented-ultrasounds on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-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: 10",
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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. -->
# robust_llm_pythia-31m_mz-132_WordLength_n-its-10
This model is a fine-tuned version of [EleutherAI/pythia-31m](https://huggingfa... | {"tags": ["generated_from_trainer"], "base_model": "EleutherAI/pythia-31m", "model-index": [{"name": "robust_llm_pythia-31m_mz-132_WordLength_n-its-10", "results": []}]} | AlignmentResearch/robust_llm_pythia-31m_mz-132_WordLength_n-its-10 | null | [
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] | null | 2024-04-24T22:14:04+00:00 | [] | [] | TAGS
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|
# robust_llm_pythia-31m_mz-132_WordLength_n-its-10
This model is a fine-tuned version of EleutherAI/pythia-31m on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedu... | [
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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. -->
# my_awesome_eli5_clm-model
This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on the eli5_cate... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["eli5_category"], "base_model": "distilgpt2", "model-index": [{"name": "my_awesome_eli5_clm-model", "results": []}]} | kathleenkatchis/my_awesome_eli5_clm-model | null | [
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| my\_awesome\_eli5\_clm-model
============================
This model is a fine-tuned version of distilgpt2 on the eli5\_category dataset.
It achieves the following results on the evaluation set:
* Loss: 3.8360
Model description
-----------------
More information needed
Intended uses & limitations
------------... | [
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text-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": []} | research-dump/roberta-large_ABLATION_hoax_classifier_defs_1h2r | null | [
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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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reinforcement-learning | null |
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
| {"tags": ["Pixelcopter-PLE-v0", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-Pixelcopter-PLE-v0-hyp", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pixelcopter-PLE-v0", "type": "Pix... | rahil1206/Reinforce-Pixelcopter-PLE-v0-hyp | null | [
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|
# Reinforce Agent playing Pixelcopter-PLE-v0
This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
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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]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned-adapters_Aleatoric_tiny_0.6_Seed101 | null | [
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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]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned_Aleatoric_tiny_0.6_Seed101 | null | [
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### Model Sources [optional]
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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. -->
# robust_llm_pythia-70m_mz-132_WordLength_n-its-10
This model is a fine-tuned version of [EleutherAI/pythia-70m](https://huggingfa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "EleutherAI/pythia-70m", "model-index": [{"name": "robust_llm_pythia-70m_mz-132_WordLength_n-its-10", "results": []}]} | AlignmentResearch/robust_llm_pythia-70m_mz-132_WordLength_n-its-10 | null | [
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|
# robust_llm_pythia-70m_mz-132_WordLength_n-its-10
This model is a fine-tuned version of EleutherAI/pythia-70m on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedu... | [
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null | fastai |
# Amazing!
🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([docume... | {"tags": ["fastai"]} | iamacaru/simpsons | null | [
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# Amazing!
Congratulations on hosting your fastai model on the Hugging Face Hub!
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text-to-image | diffusers |
# Endless Reality
1.0 version of this model with the 840KVAE baked in. Comparison:
Samples and prompts:
![Free AI image generator endless reality samples](https... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["Realism", "Scifi", "Portrait", "davcha", "stable-diffusion", "stable-diffusion-diffusers", "diffusers", "text-to-image"], "pipeline_tag": "text-to-image"} | Yntec/endlessReality | null | [
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|
# Endless Reality
1.0 version of this model with the 840KVAE baked in. Comparison:
!Free text to image endless reality comparison
Samples and prompts:
!Free AI image generator endless reality samples
Top left: detailed postcard movie perfect face, full body, baby, masterpiece, highest quality, crowd, realistic ey... | [
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null | fastai |
# Amazing!
🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([docume... | {"tags": ["fastai"]} | miibanl/CochesCamionesTrenesMotosAutobuses | null | [
"fastai",
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#fastai #has_space #region-us
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# Amazing!
Congratulations on hosting your fastai model on the Hugging Face Hub!
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1. Fill out this model card with more information (see the template below and the documentation here)!
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text-to-image | diffusers |
This Repo contains a diffusers format version of the PixArt-Sigma Repos
PixArt-alpha/pixart_sigma_sdxlvae_T5_diffusers
PixArt-alpha/PixArt-Sigma-XL-2-2K-MS
with the models loaded and saved in fp16 and bf16 formats, roughly halfing their sizes.
It can be used where download bandwith, memory or diskspace are relatively... | {"license": "openrail++"} | Vargol/PixArt-Sigma_2k_16bit | null | [
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#diffusers #safetensors #license-openrail++ #diffusers-PixArtSigmaPipeline #region-us
|
This Repo contains a diffusers format version of the PixArt-Sigma Repos
PixArt-alpha/pixart_sigma_sdxlvae_T5_diffusers
PixArt-alpha/PixArt-Sigma-XL-2-2K-MS
with the models loaded and saved in fp16 and bf16 formats, roughly halfing their sizes.
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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": []} | rizwan-ai/mistral_7b-instruct-guanaco | null | [
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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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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. -->
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image-classification | null | # Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
Using the dataset provided, only the spheroids were used for training. Detecting accuracy is below 10% and a lot of duplicates.
Version not usefull.
## Model Details
### Model Description
- **Developed by:** Jeroen den Otter
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sentence-similarity | sentence-transformers |
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model becomes easy when ... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | redscroll/msmarco-mpnet | null | [
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text-generation | transformers |
# T3Q-Llama3-8B-Inst-sft1.0
## This model is a version of meta-llama/Meta-Llama-3-8B-Instruct that has been fine-tuned with SFT.
## Model Developers Chihoon Lee(chihoonlee10), T3Q
#### Transfo... | {"license": "apache-2.0", "library_name": "transformers", "datasets": ["maywell/ko_Ultrafeedback_binarized"], "pipeline_tag": "text-generation", "base model": ["meta-llama/Meta-Llama-3-8B-Instruct"]} | chlee10/T3Q-Llama3-8B-Inst-sft1.0 | null | [
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|
!image/png
# T3Q-Llama3-8B-Inst-sft1.0
## This model is a version of meta-llama/Meta-Llama-3-8B-Instruct that has been fine-tuned with SFT.
## Model Developers Chihoon Lee(chihoonlee10), T3Q
#### Transformers pipeline
#### Transformers AutoModelForCausalLM
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unconditional-image-generation | diffusers |
# Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
This model is a diffusion model for unconditional image generation of cute 🦋.
## Usage
```python
from diffusers import DDPMPipeline
pipeline = DDPMPipeline.from_pretrained('tuandunghcmut/sd-class-butt... | {"license": "mit", "tags": ["pytorch", "diffusers", "unconditional-image-generation", "diffusion-models-class"]} | tuandunghcmut/sd-class-butterflies-32 | null | [
"diffusers",
"safetensors",
"pytorch",
"unconditional-image-generation",
"diffusion-models-class",
"license:mit",
"diffusers:DDPMPipeline",
"region:us"
] | null | 2024-04-24T22:35:38+00:00 | [] | [] | TAGS
#diffusers #safetensors #pytorch #unconditional-image-generation #diffusion-models-class #license-mit #diffusers-DDPMPipeline #region-us
|
# Model Card for Unit 1 of the Diffusion Models Class
This model is a diffusion model for unconditional image generation of cute .
## Usage
| [
"# Model Card for Unit 1 of the Diffusion Models Class \n\nThis model is a diffusion model for unconditional image generation of cute .",
"## Usage"
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"## Usage"
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"TAGS\n#diffusers #safetensors #pytorch #unconditional-image-generation #diffusion-models-class #license-mit #diffusers-DDPMPipeline #region-us \n# Model Card for Unit 1 of the Diffusion Models Class \n\nThis model is a diffusion model for unconditional image generation of cute .## Usage"
] |
null | null |
# kat33/Mixtral-8x7B-Instruct-v0.1-Q3_K_S-GGUF
This model was converted to GGUF format from [`mistralai/Mixtral-8x7B-Instruct-v0.1`](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [or... | {"language": ["fr", "it", "de", "es", "en"], "license": "apache-2.0", "tags": ["llama-cpp", "gguf-my-repo"], "inference": {"parameters": {"temperature": 0.5}}, "widget": [{"messages": [{"role": "user", "content": "What is your favorite condiment?"}]}]} | kat33/Mixtral-8x7B-Instruct-v0.1-Q3_K_S-GGUF | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"fr",
"it",
"de",
"es",
"en",
"license:apache-2.0",
"region:us"
] | null | 2024-04-24T22:39:45+00:00 | [] | [
"fr",
"it",
"de",
"es",
"en"
] | TAGS
#gguf #llama-cpp #gguf-my-repo #fr #it #de #es #en #license-apache-2.0 #region-us
|
# kat33/Mixtral-8x7B-Instruct-v0.1-Q3_K_S-GGUF
This model was converted to GGUF format from 'mistralai/Mixtral-8x7B-Instruct-v0.1' 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 server or the CLI.
... | [
"# kat33/Mixtral-8x7B-Instruct-v0.1-Q3_K_S-GGUF\nThis model was converted to GGUF format from 'mistralai/Mixtral-8x7B-Instruct-v0.1' 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\nInvoke the URL serv... | [
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"# kat33/Mixtral-8x7B-Instruct-v0.1-Q3_K_S-GGUF\nThis model was converted to GGUF format from 'mistralai/Mixtral-8x7B-Instruct-v0.1' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more ... | [
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"TAGS\n#gguf #llama-cpp #gguf-my-repo #fr #it #de #es #en #license-apache-2.0 #region-us \n# kat33/Mixtral-8x7B-Instruct-v0.1-Q3_K_S-GGUF\nThis model was converted to GGUF format from 'mistralai/Mixtral-8x7B-Instruct-v0.1' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more detail... |
null | null | # Sconfiggere l'Infezione Fungina con FungoKiller: La Chiave per Piedi Sani e Unghie Belle
L'infezione fungina delle unghie e dei piedi è un problema comune che può causare fastidi, disagio e imbarazzo. Fortunatamente, c'è una soluzione efficace disponibile: FungoKiller. In questa articolo, esploreremo i vantaggi di q... | {} | fafab34728/fungokiller-in-italia | null | [
"region:us"
] | null | 2024-04-24T22:41:46+00:00 | [] | [] | TAGS
#region-us
| # Sconfiggere l'Infezione Fungina con FungoKiller: La Chiave per Piedi Sani e Unghie Belle
L'infezione fungina delle unghie e dei piedi è un problema comune che può causare fastidi, disagio e imbarazzo. Fortunatamente, c'è una soluzione efficace disponibile: FungoKiller. In questa articolo, esploreremo i vantaggi di q... | [
"# Sconfiggere l'Infezione Fungina con FungoKiller: La Chiave per Piedi Sani e Unghie Belle\n\nL'infezione fungina delle unghie e dei piedi è un problema comune che può causare fastidi, disagio e imbarazzo. Fortunatamente, c'è una soluzione efficace disponibile: FungoKiller. In questa articolo, esploreremo i vantag... | [
"TAGS\n#region-us \n",
"# Sconfiggere l'Infezione Fungina con FungoKiller: La Chiave per Piedi Sani e Unghie Belle\n\nL'infezione fungina delle unghie e dei piedi è un problema comune che può causare fastidi, disagio e imbarazzo. Fortunatamente, c'è una soluzione efficace disponibile: FungoKiller. In questa artic... | [
5,
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125,
266,
174,
193,
25
] | [
"TAGS\n#region-us \n# Sconfiggere l'Infezione Fungina con FungoKiller: La Chiave per Piedi Sani e Unghie Belle\n\nL'infezione fungina delle unghie e dei piedi è un problema comune che può causare fastidi, disagio e imbarazzo. Fortunatamente, c'è una soluzione efficace disponibile: FungoKiller. In questa articolo, e... |
zero-shot-image-classification | transformers.js | ERROR: type should be string, got "\nhttps://github.com/apple/ml-mobileclip with ONNX weights to be compatible with Transformers.js.\n\n## Usage (Transformers.js)\n\nIf you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@xenova/transformers) using:\n```bash\nnpm i @xenova/transformers\n```\n\n**Example:** Perform zero-shot image classification.\n```js\nimport {\n AutoTokenizer,\n CLIPTextModelWithProjection,\n AutoProcessor,\n CLIPVisionModelWithProjection,\n RawImage,\n dot,\n softmax,\n} from '@xenova/transformers';\n\nconst model_id = 'Xenova/mobileclip_s0';\n\n// Load tokenizer and text model\nconst tokenizer = await AutoTokenizer.from_pretrained(model_id);\nconst text_model = await CLIPTextModelWithProjection.from_pretrained(model_id);\n\n// Load processor and vision model\nconst processor = await AutoProcessor.from_pretrained(model_id);\nconst vision_model = await CLIPVisionModelWithProjection.from_pretrained(model_id, {\n quantized: false, // NOTE: vision model is sensitive to quantization.\n});\n\n// Run tokenization\nconst texts = ['cats', 'dogs', 'birds'];\nconst text_inputs = tokenizer(texts, { padding: 'max_length', truncation: true });\n\n// Compute text embeddings\nconst { text_embeds } = await text_model(text_inputs);\nconst normalized_text_embeds = text_embeds.normalize().tolist();\n\n// Read image and run processor\nconst url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg';\nconst image = await RawImage.read(url);\nconst image_inputs = await processor(image);\n\n// Compute vision embeddings\nconst { image_embeds } = await vision_model(image_inputs);\nconst normalized_image_embeds = image_embeds.normalize().tolist();\n\n// Compute probabilities\nconst probabilities = normalized_image_embeds.map(\n x => softmax(normalized_text_embeds.map(y => 100 * dot(x, y)))\n);\nconsole.log(probabilities); // [[ 0.9989384093386391, 0.001060433633052551, 0.000001157028308360134 ]]\n```\n" | {"license": "other", "library_name": "transformers.js", "tags": ["mobileclip", "image-feature-extraction", "feature-extraction"], "pipeline_tag": "zero-shot-image-classification"} | Xenova/mobileclip_s0 | null | [
"transformers.js",
"onnx",
"clip",
"mobileclip",
"image-feature-extraction",
"feature-extraction",
"zero-shot-image-classification",
"license:other",
"region:us"
] | null | 2024-04-24T22:41:51+00:00 | [] | [] | TAGS
#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us
|
URL with ONNX weights to be compatible with URL.
## Usage (URL)
If you haven't already, you can install the URL JavaScript library from NPM using:
Example: Perform zero-shot image classification.
| [
"## Usage (URL)\n\nIf you haven't already, you can install the URL JavaScript library from NPM using:\n\n\nExample: Perform zero-shot image classification."
] | [
"TAGS\n#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us \n",
"## Usage (URL)\n\nIf you haven't already, you can install the URL JavaScript library from NPM using:\n\n\nExample: Perform zero-shot image classification."
... | [
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"TAGS\n#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us \n## Usage (URL)\n\nIf you haven't already, you can install the URL JavaScript library from NPM using:\n\n\nExample: Perform zero-shot image classification."
] |
zero-shot-image-classification | transformers.js | ERROR: type should be string, got "\nhttps://github.com/apple/ml-mobileclip with ONNX weights to be compatible with Transformers.js.\n\n## Usage (Transformers.js)\n\nIf you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@xenova/transformers) using:\n```bash\nnpm i @xenova/transformers\n```\n\n**Example:** Perform zero-shot image classification.\n```js\nimport {\n AutoTokenizer,\n CLIPTextModelWithProjection,\n AutoProcessor,\n CLIPVisionModelWithProjection,\n RawImage,\n dot,\n softmax,\n} from '@xenova/transformers';\n\nconst model_id = 'Xenova/mobileclip_s1';\n\n// Load tokenizer and text model\nconst tokenizer = await AutoTokenizer.from_pretrained(model_id);\nconst text_model = await CLIPTextModelWithProjection.from_pretrained(model_id);\n\n// Load processor and vision model\nconst processor = await AutoProcessor.from_pretrained(model_id);\nconst vision_model = await CLIPVisionModelWithProjection.from_pretrained(model_id, {\n quantized: false, // NOTE: vision model is sensitive to quantization.\n});\n\n// Run tokenization\nconst texts = ['cats', 'dogs', 'birds'];\nconst text_inputs = tokenizer(texts, { padding: 'max_length', truncation: true });\n\n// Compute text embeddings\nconst { text_embeds } = await text_model(text_inputs);\nconst normalized_text_embeds = text_embeds.normalize().tolist();\n\n// Read image and run processor\nconst url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg';\nconst image = await RawImage.read(url);\nconst image_inputs = await processor(image);\n\n// Compute vision embeddings\nconst { image_embeds } = await vision_model(image_inputs);\nconst normalized_image_embeds = image_embeds.normalize().tolist();\n\n// Compute probabilities\nconst probabilities = normalized_image_embeds.map(\n x => softmax(normalized_text_embeds.map(y => 100 * dot(x, y)))\n);\nconsole.log(probabilities); // [[ 0.9999744722905349, 0.0000217474276948055, 0.00000378028177032859 ]]\n```\n" | {"license": "other", "library_name": "transformers.js", "tags": ["mobileclip", "image-feature-extraction", "feature-extraction"], "pipeline_tag": "zero-shot-image-classification"} | Xenova/mobileclip_s1 | null | [
"transformers.js",
"onnx",
"clip",
"mobileclip",
"image-feature-extraction",
"feature-extraction",
"zero-shot-image-classification",
"license:other",
"region:us"
] | null | 2024-04-24T22:42:01+00:00 | [] | [] | TAGS
#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us
|
URL with ONNX weights to be compatible with URL.
## Usage (URL)
If you haven't already, you can install the URL JavaScript library from NPM using:
Example: Perform zero-shot image classification.
| [
"## Usage (URL)\n\nIf you haven't already, you can install the URL JavaScript library from NPM using:\n\n\nExample: Perform zero-shot image classification."
] | [
"TAGS\n#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us \n",
"## Usage (URL)\n\nIf you haven't already, you can install the URL JavaScript library from NPM using:\n\n\nExample: Perform zero-shot image classification."
... | [
41,
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"TAGS\n#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us \n## Usage (URL)\n\nIf you haven't already, you can install the URL JavaScript library from NPM using:\n\n\nExample: Perform zero-shot image classification."
] |
zero-shot-image-classification | transformers.js | ERROR: type should be string, got "\nhttps://github.com/apple/ml-mobileclip with ONNX weights to be compatible with Transformers.js.\n\n## Usage (Transformers.js)\n\nIf you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@xenova/transformers) using:\n```bash\nnpm i @xenova/transformers\n```\n\n**Example:** Perform zero-shot image classification.\n```js\nimport {\n AutoTokenizer,\n CLIPTextModelWithProjection,\n AutoProcessor,\n CLIPVisionModelWithProjection,\n RawImage,\n dot,\n softmax,\n} from '@xenova/transformers';\n\nconst model_id = 'Xenova/mobileclip_s2';\n\n// Load tokenizer and text model\nconst tokenizer = await AutoTokenizer.from_pretrained(model_id);\nconst text_model = await CLIPTextModelWithProjection.from_pretrained(model_id);\n\n// Load processor and vision model\nconst processor = await AutoProcessor.from_pretrained(model_id);\nconst vision_model = await CLIPVisionModelWithProjection.from_pretrained(model_id, {\n quantized: false, // NOTE: vision model is sensitive to quantization.\n});\n\n// Run tokenization\nconst texts = ['cats', 'dogs', 'birds'];\nconst text_inputs = tokenizer(texts, { padding: 'max_length', truncation: true });\n\n// Compute text embeddings\nconst { text_embeds } = await text_model(text_inputs);\nconst normalized_text_embeds = text_embeds.normalize().tolist();\n\n// Read image and run processor\nconst url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg';\nconst image = await RawImage.read(url);\nconst image_inputs = await processor(image);\n\n// Compute vision embeddings\nconst { image_embeds } = await vision_model(image_inputs);\nconst normalized_image_embeds = image_embeds.normalize().tolist();\n\n// Compute probabilities\nconst probabilities = normalized_image_embeds.map(\n x => softmax(normalized_text_embeds.map(y => 100 * dot(x, y)))\n);\nconsole.log(probabilities); // [[ 0.9999973851268408, 0.000002399646544186113, 2.1522661499262862e-7 ]]\n```\n" | {"license": "other", "library_name": "transformers.js", "tags": ["mobileclip", "image-feature-extraction", "feature-extraction"], "pipeline_tag": "zero-shot-image-classification"} | Xenova/mobileclip_s2 | null | [
"transformers.js",
"onnx",
"clip",
"mobileclip",
"image-feature-extraction",
"feature-extraction",
"zero-shot-image-classification",
"license:other",
"region:us"
] | null | 2024-04-24T22:42:10+00:00 | [] | [] | TAGS
#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us
|
URL with ONNX weights to be compatible with URL.
## Usage (URL)
If you haven't already, you can install the URL JavaScript library from NPM using:
Example: Perform zero-shot image classification.
| [
"## Usage (URL)\n\nIf you haven't already, you can install the URL JavaScript library from NPM using:\n\n\nExample: Perform zero-shot image classification."
] | [
"TAGS\n#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us \n",
"## Usage (URL)\n\nIf you haven't already, you can install the URL JavaScript library from NPM using:\n\n\nExample: Perform zero-shot image classification."
... | [
41,
37
] | [
"TAGS\n#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us \n## Usage (URL)\n\nIf you haven't already, you can install the URL JavaScript library from NPM using:\n\n\nExample: Perform zero-shot image classification."
] |
zero-shot-image-classification | transformers.js | ERROR: type should be string, got "\nhttps://github.com/apple/ml-mobileclip with ONNX weights to be compatible with Transformers.js.\n\n## Usage (Transformers.js)\n\nIf you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@xenova/transformers) using:\n```bash\nnpm i @xenova/transformers\n```\n\n**Example:** Perform zero-shot image classification.\n```js\nimport {\n AutoTokenizer,\n CLIPTextModelWithProjection,\n AutoProcessor,\n CLIPVisionModelWithProjection,\n RawImage,\n dot,\n softmax,\n} from '@xenova/transformers';\n\nconst model_id = 'Xenova/mobileclip_b';\n\n// Load tokenizer and text model\nconst tokenizer = await AutoTokenizer.from_pretrained(model_id);\nconst text_model = await CLIPTextModelWithProjection.from_pretrained(model_id);\n\n// Load processor and vision model\nconst processor = await AutoProcessor.from_pretrained(model_id);\nconst vision_model = await CLIPVisionModelWithProjection.from_pretrained(model_id, {\n quantized: false, // NOTE: vision model is sensitive to quantization.\n});\n\n// Run tokenization\nconst texts = ['cats', 'dogs', 'birds'];\nconst text_inputs = tokenizer(texts, { padding: 'max_length', truncation: true });\n\n// Compute text embeddings\nconst { text_embeds } = await text_model(text_inputs);\nconst normalized_text_embeds = text_embeds.normalize().tolist();\n\n// Read image and run processor\nconst url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg';\nconst image = await RawImage.read(url);\nconst image_inputs = await processor(image);\n\n// Compute vision embeddings\nconst { image_embeds } = await vision_model(image_inputs);\nconst normalized_image_embeds = image_embeds.normalize().tolist();\n\n// Compute probabilities\nconst probabilities = normalized_image_embeds.map(\n x => softmax(normalized_text_embeds.map(y => 100 * dot(x, y)))\n);\nconsole.log(probabilities); // [[ 0.999993040175817, 0.000006828091823929405, 1.3173235896278122e-7 ]]\n```\n" | {"license": "other", "library_name": "transformers.js", "tags": ["mobileclip", "image-feature-extraction", "feature-extraction"], "pipeline_tag": "zero-shot-image-classification"} | Xenova/mobileclip_b | null | [
"transformers.js",
"onnx",
"clip",
"mobileclip",
"image-feature-extraction",
"feature-extraction",
"zero-shot-image-classification",
"license:other",
"region:us"
] | null | 2024-04-24T22:42:21+00:00 | [] | [] | TAGS
#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us
|
URL with ONNX weights to be compatible with URL.
## Usage (URL)
If you haven't already, you can install the URL JavaScript library from NPM using:
Example: Perform zero-shot image classification.
| [
"## Usage (URL)\n\nIf you haven't already, you can install the URL JavaScript library from NPM using:\n\n\nExample: Perform zero-shot image classification."
] | [
"TAGS\n#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us \n",
"## Usage (URL)\n\nIf you haven't already, you can install the URL JavaScript library from NPM using:\n\n\nExample: Perform zero-shot image classification."
... | [
41,
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] | [
"TAGS\n#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us \n## Usage (URL)\n\nIf you haven't already, you can install the URL JavaScript library from NPM using:\n\n\nExample: Perform zero-shot image classification."
] |
zero-shot-image-classification | transformers.js | ERROR: type should be string, got "\nhttps://github.com/apple/ml-mobileclip with ONNX weights to be compatible with Transformers.js.\n\n## Usage (Transformers.js)\n\nIf you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@xenova/transformers) using:\n```bash\nnpm i @xenova/transformers\n```\n\n**Example:** Perform zero-shot image classification.\n```js\nimport {\n AutoTokenizer,\n CLIPTextModelWithProjection,\n AutoProcessor,\n CLIPVisionModelWithProjection,\n RawImage,\n dot,\n softmax,\n} from '@xenova/transformers';\n\nconst model_id = 'Xenova/mobileclip_blt';\n\n// Load tokenizer and text model\nconst tokenizer = await AutoTokenizer.from_pretrained(model_id);\nconst text_model = await CLIPTextModelWithProjection.from_pretrained(model_id);\n\n// Load processor and vision model\nconst processor = await AutoProcessor.from_pretrained(model_id);\nconst vision_model = await CLIPVisionModelWithProjection.from_pretrained(model_id, {\n quantized: false, // NOTE: vision model is sensitive to quantization.\n});\n\n// Run tokenization\nconst texts = ['cats', 'dogs', 'birds'];\nconst text_inputs = tokenizer(texts, { padding: 'max_length', truncation: true });\n\n// Compute text embeddings\nconst { text_embeds } = await text_model(text_inputs);\nconst normalized_text_embeds = text_embeds.normalize().tolist();\n\n// Read image and run processor\nconst url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg';\nconst image = await RawImage.read(url);\nconst image_inputs = await processor(image);\n\n// Compute vision embeddings\nconst { image_embeds } = await vision_model(image_inputs);\nconst normalized_image_embeds = image_embeds.normalize().tolist();\n\n// Compute probabilities\nconst probabilities = normalized_image_embeds.map(\n x => softmax(normalized_text_embeds.map(y => 100 * dot(x, y)))\n);\nconsole.log(probabilities); // [[ 0.9999057403656509, 0.00009141888000214805, 0.0000028407543469763894 ]]\n```\n" | {"license": "other", "library_name": "transformers.js", "tags": ["mobileclip", "image-feature-extraction", "feature-extraction"], "pipeline_tag": "zero-shot-image-classification"} | Xenova/mobileclip_blt | null | [
"transformers.js",
"onnx",
"clip",
"mobileclip",
"image-feature-extraction",
"feature-extraction",
"zero-shot-image-classification",
"license:other",
"region:us",
"has_space"
] | null | 2024-04-24T22:42:37+00:00 | [] | [] | TAGS
#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us #has_space
|
URL with ONNX weights to be compatible with URL.
## Usage (URL)
If you haven't already, you can install the URL JavaScript library from NPM using:
Example: Perform zero-shot image classification.
| [
"## Usage (URL)\n\nIf you haven't already, you can install the URL JavaScript library from NPM using:\n\n\nExample: Perform zero-shot image classification."
] | [
"TAGS\n#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us #has_space \n",
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] | [
"TAGS\n#transformers.js #onnx #clip #mobileclip #image-feature-extraction #feature-extraction #zero-shot-image-classification #license-other #region-us #has_space \n## Usage (URL)\n\nIf you haven't already, you can install the URL JavaScript library from NPM using:\n\n\nExample: Perform zero-shot image classificati... |
null | null |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
## Mo... | {} | Ingvarus/BotAl | null | [
"arxiv:1910.09700",
"region:us"
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"1910.09700"
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#arxiv-1910.09700 #region-us
|
# Model Card for Model ID
This modelcard aims to be a base template for new models. It has been generated using this raw template.
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null | transformers |
# Model Card for Model ID
Note only a text gen but also chatbot, I'm just test and...it's work, very nice, try it.
## Model Details
- [](https://colab.research.google.com/drive/1mWRFts7yCErqHeBzsaQ3vNDkyg1rKszX?usp=sharing)
### Model Descript... | {"license": "apache-2.0", "library_name": "transformers"} | HuyRemy/chatphil | null | [
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"safetensors",
"license:apache-2.0",
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"region:us"
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#transformers #safetensors #license-apache-2.0 #endpoints_compatible #region-us
|
# Model Card for Model ID
Note only a text gen but also chatbot, I'm just test and...it's work, very nice, try it.
## Model Details
- ![Open In Colab](URL
### Model Description
This is the model card of a transformers model that has been pushed on the Hub.
- Developed by: HuyRemy
- Funded by : HuyRemy
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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. -->
# swinv2-tiny-patch4-window8-256-dmae-va-U5-42C
This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](h... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/swinv2-tiny-patch4-window8-256", "model-index": [{"name": "swinv2-tiny-patch4-window8-256-dmae-va-U5-42C", "results": []}]} | Augusto777/swinv2-tiny-patch4-window8-256-dmae-va-U5-42C | null | [
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| swinv2-tiny-patch4-window8-256-dmae-va-U5-42C
=============================================
This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7073
* Accuracy: 0.7667
Model description
-----------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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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": []} | LongQ/Mistral_8x7B_SFT_Lora | 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-classification | setfit |
# SetFit with FacebookAI/roberta-base
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) as the Sentence Transformer embedding model. A [LogisticRegression](https://s... | {"library_name": "setfit", "tags": ["setfit", "sentence-transformers", "text-classification", "generated_from_setfit_trainer"], "metrics": ["accuracy"], "base_model": "FacebookAI/roberta-base", "widget": [{"text": "Just checking in, how have you been feeling since our last chat?"}, {"text": "I\u2019m looking forward to... | richie-ghost/setfit-FacebookAI-roberta-base-phatic | null | [
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| SetFit with FacebookAI/roberta-base
===================================
This is a SetFit model that can be used for Text Classification. This SetFit model uses FacebookAI/roberta-base as the Sentence Transformer embedding model. A LogisticRegression instance is used for classification.
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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]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned-adapters_Aleatoric_tiny_0.6_Seed102 | null | [
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"region:us"
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"1910.09700"
] | [] | TAGS
#peft #arxiv-1910.09700 #base_model-TinyLlama/TinyLlama-1.1B-Chat-v1.0 #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
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### Direct Use
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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]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned_Aleatoric_tiny_0.6_Seed102 | null | [
"peft",
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|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
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### Direct Use
... | [
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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": ["trl", "sft"]} | Smulemun/RuNNER-v1 | null | [
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"arxiv:1910.09700",
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"endpoints_compatible",
"text-generation-inference",
"4-bit",
"region:us"
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"1910.09700"
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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]:
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text-to-image | diffusers |
# shiratakimix-xl API Inference
## Get API Key
Get API key from [ModelsLab API](http://modelslab.com), No Payment needed.
Replace Key in below code, change **mod... | {"license": "creativeml-openrail-m", "tags": ["modelslab.com", "stable-diffusion-api", "text-to-image", "ultra-realistic"], "pinned": true} | stablediffusionapi/shiratakimix-xl | null | [
"diffusers",
"modelslab.com",
"stable-diffusion-api",
"text-to-image",
"ultra-realistic",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | null | 2024-04-24T23:06:49+00:00 | [] | [] | TAGS
#diffusers #modelslab.com #stable-diffusion-api #text-to-image #ultra-realistic #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionXLPipeline #region-us
|
# shiratakimix-xl API Inference
!generated from URL
## Get API Key
Get API key from ModelsLab API, No Payment needed.
Replace Key in below code, change model_id to "shiratakimix-xl"
Coding in PHP/Node/Java etc? Have a look at docs for more code examples: View docs
Try model for free: Generate Images
Model link... | [
"# shiratakimix-xl API Inference\n\n!generated from URL",
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reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **PandaReachDense-v3**
This is a trained model of a **A2C** agent playing **PandaReachDense-v3**
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 huggingf... | {"library_name": "stable-baselines3", "tags": ["PandaReachDense-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "PandaReachDense-v3", "type":... | PabloVD/a2c-PandaReachDense-v3 | null | [
"stable-baselines3",
"PandaReachDense-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-24T23:08:43+00:00 | [] | [] | TAGS
#stable-baselines3 #PandaReachDense-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing PandaReachDense-v3
This is a trained model of a A2C agent playing PandaReachDense-v3
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# A2C Agent playing PandaReachDense-v3\nThis is a trained model of a A2C agent playing PandaReachDense-v3\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #PandaReachDense-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing PandaReachDense-v3\nThis is a trained model of a A2C agent playing PandaReachDense-v3\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nT... | [
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"TAGS\n#stable-baselines3 #PandaReachDense-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n# A2C Agent playing PandaReachDense-v3\nThis is a trained model of a A2C agent playing PandaReachDense-v3\nusing the stable-baselines3 library.## Usage (with Stable-baselines3)\nTODO: Add you... |
text-generation | transformers |
# Uploaded model
- **Developed by:** ale045
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/ma... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | ale045/llama3_unsloth | null | [
"transformers",
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"base_model:unsloth/llama-3-8b-bnb-4bit",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-24T23:08:56+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #llama #text-generation #text-generation-inference #unsloth #trl #en #base_model-unsloth/llama-3-8b-bnb-4bit #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# Uploaded model
- Developed by: ale045
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
"# Uploaded model\n\n- Developed by: ale045\n- License: apache-2.0\n- Finetuned from model : unsloth/llama-3-8b-bnb-4bit\n\nThis llama model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #text-generation-inference #unsloth #trl #en #base_model-unsloth/llama-3-8b-bnb-4bit #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# Uploaded model\n\n- Developed by: ale045\n- License: apache-2.0\n- Finetuned from model... | [
73,
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"TAGS\n#transformers #safetensors #llama #text-generation #text-generation-inference #unsloth #trl #en #base_model-unsloth/llama-3-8b-bnb-4bit #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# Uploaded model\n\n- Developed by: ale045\n- License: apache-2.0\n- Finetuned from model : uns... |
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. -->
# robust_llm_pythia-14m_mz-132_WordLength_n-its-10
This model is a fine-tuned version of [EleutherAI/pythia-14m](https://huggingfa... | {"tags": ["generated_from_trainer"], "base_model": "EleutherAI/pythia-14m", "model-index": [{"name": "robust_llm_pythia-14m_mz-132_WordLength_n-its-10", "results": []}]} | AlignmentResearch/robust_llm_pythia-14m_mz-132_WordLength_n-its-10 | null | [
"transformers",
"tensorboard",
"safetensors",
"gpt_neox",
"text-classification",
"generated_from_trainer",
"base_model:EleutherAI/pythia-14m",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-24T23:09:38+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #gpt_neox #text-classification #generated_from_trainer #base_model-EleutherAI/pythia-14m #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# robust_llm_pythia-14m_mz-132_WordLength_n-its-10
This model is a fine-tuned version of EleutherAI/pythia-14m on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedu... | [
"# robust_llm_pythia-14m_mz-132_WordLength_n-its-10\n\nThis model is a fine-tuned version of EleutherAI/pythia-14m on an unknown dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information neede... | [
"TAGS\n#transformers #tensorboard #safetensors #gpt_neox #text-classification #generated_from_trainer #base_model-EleutherAI/pythia-14m #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# robust_llm_pythia-14m_mz-132_WordLength_n-its-10\n\nThis model is a fine-tuned version o... | [
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"TAGS\n#transformers #tensorboard #safetensors #gpt_neox #text-classification #generated_from_trainer #base_model-EleutherAI/pythia-14m #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# robust_llm_pythia-14m_mz-132_WordLength_n-its-10\n\nThis model is a fine-tuned version of Eleu... |
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