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text-generation | transformers | llava-v1.5 mixed with SoM data (20k qa)
| {} | zzxslp/som-llava-v1.5-13b-qa | null | [
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text-generation | transformers |
# Mistral-8x7b-Quantized-portuguese-luanaa
<p align="center">
<img src="https://raw.githubusercontent.com/rhaymisonbetini/huggphotos/main/24.webp" width="50%" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
</p>
This model was trained with a superset of 300,000 instructions in Portuguese.
The mo... | {"language": ["pt"], "license": "apache-2.0", "library_name": "transformers", "tags": ["mixtral", "portuguese", "portugues"], "datasets": ["rhaymison/superset"], "base_model": "mistralai/Mixtral-8x7B-Instruct-v0.1", "pipeline_tag": "text-generation", "model-index": [{"name": "Mistral-8x7b-portuguese-luana", "results": ... | rhaymison/Mistral-8x7b-Quantized-portuguese-luana | null | [
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| Mistral-8x7b-Quantized-portuguese-luanaa
========================================
This model was trained with a superset of 300,000 instructions in Portuguese.
The model comes to help fill the gap in models in Portuguese.
Tuned from the Mistral 8x7b and quantized in 4bit for Portuguese, the model ... | [
"### A100 GPU\n\n\nYou can use the model in its normal form up to 4-bit quantization. Below we will use both approaches.\nRemember that verbs are important in your prompt. Tell your model how to act or behave so that you can guide them along the path of their response.\nImportant points like these help models (even... | [
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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": []} | tomaszki/stablelm-40 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers | Hello Nurse 11b quantized at 3.5bpw in EXL2 format. Original model - https://huggingface.co/MarsupialAI/HelloNurse-11b | {} | MarsupialAI/HelloNurse-11b_3.5bpw_exl2 | null | [
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text-generation | null |
# Meta Llama 3 70B Instruct - llamafile
This repository contains executable weights (which we call
[llamafiles](https://github.com/Mozilla-Ocho/llamafile)) that run on
Linux, MacOS, Windows, FreeBSD, OpenBSD, and NetBSD for AMD64 and ARM64.
- Model creator: [Meta](https://llama.meta.com/)
- Original model: [meta-lla... | {"language": ["en"], "license": "other", "tags": ["llama", "llama-3", "llamafile"], "model_creator": "Meta", "quantized_by": "jartine", "base_model": "meta-llama/Meta-Llama-3-70B-Instruct", "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE", "prompt_template": "<|begin_of_text|><|sta... | jartine/Meta-Llama-3-70B-Instruct-llamafile | null | [
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| Meta Llama 3 70B Instruct - llamafile
=====================================
This repository contains executable weights (which we call
llamafiles) that run on
Linux, MacOS, Windows, FreeBSD, OpenBSD, and NetBSD for AMD64 and ARM64.
* Model creator: Meta
* Original model: meta-llama/Meta-Llama-3-70B-Instruct
Quick... | [
"### Use with transformers\n\n\nSee the snippet below for usage with Transformers:",
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text-classification | transformers | ## Metrics
- loss: 0.8263
- accuracy: 0.7947
- precision: 0.7915
- recall: 0.7947
- precision_macro: 0.5673
- recall_macro: 0.5767
- macro_fpr: 0.0183
- weighted_fpr: 0.0181
- weighted_specificity: 0.9749
- macro_specificity: 0.9846
- weighted_sensitivity: 0.7947
- macro_sensitivity: 0.5767
- f1_micro: 0.7947
- f1_mac... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "xshubhamx/legal-bert-base-uncased", "xshubhamx/InLegalBERT"]} | xshubhamx/legal-InLegal-merge-slerp | null | [
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| ## Metrics
- loss: 0.8263
- accuracy: 0.7947
- precision: 0.7915
- recall: 0.7947
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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": []} | lingchensanwen/tiny-llama-generation-best-balanced-new | 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]
- **Funded by [optional]:** [More Information Needed]
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null | transformers |
# 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 |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | domenicrosati/adversarial_loss_lr_1e-5_attack_meta-llama_Llama-2-7b-chat-hf_4_6e-5_1k | null | [
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# Model Card for Model ID
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text-classification | transformers | ## Metrics
- loss: 0.6616
- accuracy: 0.8443
- precision: 0.8473
- recall: 0.8443
- precision_macro: 0.8200
- recall_macro: 0.7913
- macro_fpr: 0.0134
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- macro_specificity: 0.9883
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- f1_micro: 0.8443
- f1_mac... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "xshubhamx/legal-bert-base-uncased", "xshubhamx/InLegalBERT"]} | xshubhamx/legal-InLegal-merge-ties | null | [
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"xshubhamx/InLegalBERT",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-19T21:05:50+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #bert #text-classification #merge #mergekit #lazymergekit #xshubhamx/legal-bert-base-uncased #xshubhamx/InLegalBERT #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| ## Metrics
- loss: 0.6616
- accuracy: 0.8443
- precision: 0.8473
- recall: 0.8443
- precision_macro: 0.8200
- recall_macro: 0.7913
- macro_fpr: 0.0134
- weighted_fpr: 0.0130
- weighted_specificity: 0.9802
- macro_specificity: 0.9883
- weighted_sensitivity: 0.8443
- macro_sensitivity: 0.7913
- f1_micro: 0.8443
- f1_mac... | [
"## Metrics\n\n- loss: 0.6616\n- accuracy: 0.8443\n- precision: 0.8473\n- recall: 0.8443\n- precision_macro: 0.8200\n- recall_macro: 0.7913\n- macro_fpr: 0.0134\n- weighted_fpr: 0.0130\n- weighted_specificity: 0.9802\n- macro_specificity: 0.9883\n- weighted_sensitivity: 0.8443\n- macro_sensitivity: 0.7913\n- f1_mic... | [
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reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **CartPole-v1**
This is a trained model of a **DQN** agent playing **CartPole-v1**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 import... | {"library_name": "stable-baselines3", "tags": ["CartPole-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CartPole-v1", "type": "CartPole-v1"... | CrispyJLoHalo/dqn-CartPole-v1_2 | null | [
"stable-baselines3",
"CartPole-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-19T21:06:01+00:00 | [] | [] | TAGS
#stable-baselines3 #CartPole-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing CartPole-v1
This is a trained model of a DQN agent playing CartPole-v1
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
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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. -->
# peft-dialogue-summary-training-1713727973
This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microso... | {"license": "mit", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "microsoft/phi-2", "model-index": [{"name": "peft-dialogue-summary-training-1713727973", "results": []}]} | medvediev/peft-dialogue-summary-training-1713727973 | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:microsoft/phi-2",
"license:mit",
"region:us"
] | null | 2024-04-19T21:08:45+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-microsoft/phi-2 #license-mit #region-us
| peft-dialogue-summary-training-1713727973
=========================================
This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.3302
Model description
-----------------
More information needed
Intended uses & l... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 4\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1... | [
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text-generation | mlx |
# Meta-Llama-3-8B-4bit-conversation-finetuned
This model was converted to MLX format from [`meta-llama/Meta-Llama-3-8B`]().
Refer to the [original model card](https://huggingface.co/meta-llama/Meta-Llama-3-8B) for more details on the model.
## Use with mlx
```bash
pip install mlx
git clone https://github.com/ml-explor... | {"language": ["en"], "license": "other", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3", "mlx"], "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\"A... | mlx-community/Meta-Llama-3-8B-4bit-conversation-finetuned | null | [
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"facebook",
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"text-generation",
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"region:us"
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"en"
] | TAGS
#mlx #safetensors #llama #facebook #meta #pytorch #llama-3 #text-generation #conversational #en #license-other #region-us
|
# Meta-Llama-3-8B-4bit-conversation-finetuned
This model was converted to MLX format from ['meta-llama/Meta-Llama-3-8B']().
Refer to the original model card for more details on the model.
## Use with mlx
| [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | gaurav021201/Meta-Llama-3-8B-GPTQ | null | [
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#transformers #pytorch #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #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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fill-mask | 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": []} | quastrinos/deberta-v3-large-finetuned-mlm-accelerate-v2-xp-1 | null | [
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# Model Card for Model ID
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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
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
MoM: Mixture of Mixture
This Model is a first test to combine [Jamba](https://huggingface.co/ai21labs/Jamba-v0.1) architecture with bf16 bits linear layers, mixture of attention head and mixtu... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["moe", "moah", "mod"], "datasets": ["Locutusque/UltraTextbooks"]} | Ostixe360/MoMv4-bf16 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
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null | adapter-transformers |
# Adapter `BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_0` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_MICRO_helpfulness_dataset](https://huggingface.co/datasets/BigTMiami/amazon_MICRO_helpfulness_dataset/) dataset and i... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_MICRO_helpfulness_dataset"]} | BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_0 | null | [
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"dataset:BigTMiami/amazon_MICRO_helpfulness_dataset",
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#adapter-transformers #roberta #dataset-BigTMiami/amazon_MICRO_helpfulness_dataset #region-us
|
# Adapter 'BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_0' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_MICRO_helpfulness_dataset dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters libr... | [
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text-generation | transformers |
# Aplite-Instruct-4x8B-Llama-3
Aplite-Instruct-4x8B-Llama-3 is a experimental MoE (Mixture of Experts) model based on the Llama-3 architecture using Mergekit.
**GGUF Quant [Here](https://huggingfa... | {"language": ["en"], "license": "other", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3", "moe", "code"], "base_model": "meta-llama/Meta-Llama-3-8B-Instruct", "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE"} | raincandy-u/Llama-3-Aplite-Instruct-4x8B-MoE | null | [
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|
!image/png
# Aplite-Instruct-4x8B-Llama-3
Aplite-Instruct-4x8B-Llama-3 is a experimental MoE (Mixture of Experts) model based on the Llama-3 architecture using Mergekit.
GGUF Quant Here or (Made by mradermacher)
EXL2 Quant Here (Thanks to help of @Knightcodin)
<|eot_id|> bug has been fixed.
## Disclaimer
This ... | [
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text-generation | transformers | # Aura L3
The next evolution in Aura models, trained on 6 separate datasets and ready to bring you to your knees.
I am so happy to be one of the first with a finetune of this amazing model. I hope t... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers"} | ResplendentAI/Aura_L3_8B | null | [
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| # Aura L3
!image/png
The next evolution in Aura models, trained on 6 separate datasets and ready to bring you to your knees.
I am so happy to be one of the first with a finetune of this amazing model. I hope that you all enjoy the finetune as much as I know I will. | [
"# Aura L3\n\n!image/png\n\nThe next evolution in Aura models, trained on 6 separate datasets and ready to bring you to your knees.\n\nI am so happy to be one of the first with a finetune of this amazing model. I hope that you all enjoy the finetune as much as I know I will."
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reinforcement-learning | sample-factory |
A(n) **APPO** model trained on the **doom_health_gathering_supreme** environment.
This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory.
Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/
## Downloading the model
After installing Sa... | {"library_name": "sample-factory", "tags": ["deep-reinforcement-learning", "reinforcement-learning", "sample-factory"], "model-index": [{"name": "APPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "doom_health_gathering_supreme", "type": "doom_health_ga... | joen2010/rl_course_vizdoom_health_gathering_supreme | null | [
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|
A(n) APPO model trained on the doom_health_gathering_supreme environment.
This model was trained using Sample-Factory 2.0: URL
Documentation for how to use Sample-Factory can be found at URL
## Downloading the model
After installing Sample-Factory, download the model with:
## Using the model
To run the mod... | [
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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": []} | DangerMan1/my-finetuned-bert | 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 | 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. -->
# RM-HH-Gemma_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenTrue
This model is a fine-tuned version of [google/gemma-2b](h... | {"license": "gemma", "library_name": "peft", "tags": ["trl", "reward-trainer", "generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/gemma-2b", "model-index": [{"name": "RM-HH-Gemma_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenTrue", "results": []}]} | Holarissun/RM-HH-Gemma_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenTrue | null | [
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| RM-HH-Gemma\_harmless\_gpt3\_20000\_gemma2b\_shuffleFalse\_extractchosenTrue
============================================================================
This model is a fine-tuned version of google/gemma-2b on the None dataset.
It achieves the following results on the evaluation set:
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* Accuracy: 0.9... | [
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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. -->
# TinyLlama-1.1B-Chat-v1.0-wikitext2
This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingfac... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0", "model-index": [{"name": "TinyLlama-1.1B-Chat-v1.0-wikitext2", "results": []}]} | NeverLearn/TinyLlama-1.1B-Chat-v1.0-wikitext2 | null | [
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|
# TinyLlama-1.1B-Chat-v1.0-wikitext2
This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-Chat-v1.0 on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
... | [
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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. -->
# gpt2-reviews
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the fo... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "gpt2", "model-index": [{"name": "gpt2-reviews", "results": []}]} | ag2003/gpt2-reviews | null | [
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| gpt2-reviews
============
This model is a fine-tuned version of gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0751
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Tr... | [
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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": []} | mridul161203/Meta-llama-3-8B-GPTQ | null | [
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# Model Card for Model ID
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | adapter-transformers |
# Adapter `BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_1` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_MICRO_helpfulness_dataset](https://huggingface.co/datasets/BigTMiami/amazon_MICRO_helpfulness_dataset/) dataset and i... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_MICRO_helpfulness_dataset"]} | BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_1 | null | [
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An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_MICRO_helpfulness_dataset dataset and includes a prediction head for classification.
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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Medium GA-EN Speech Translation
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/ope... | {"language": ["ga", "en"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["ymoslem/IWSLT2023-GA-EN", "ymoslem/FLEURS-GA-EN", "ymoslem/BitesizeIrish-GA-EN", "ymoslem/SpokenWords-GA-EN-MTed", "ymoslem/Tatoeba-Speech-Irish", "ymoslem/Wikimedia-Speech-Irish"], "metrics": ["bleu", "wer"], "base_mo... | ymoslem/whisper-medium-ga2en-v4 | null | [
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"dataset:ymoslem/... | null | 2024-04-19T21:25:49+00:00 | [] | [
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=======================================
This model is a fine-tuned version of openai/whisper-medium on the IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia, augmented with noise dataset.
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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": []} | ag2003/gpt2-finetuned-IR-Ass4 | 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": []} | daisysxm76/gpt2-xl-Memit-anti-stereoset-v1 | null | [
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text-to-image | diffusers |
# Juggernaut X v10 + RunDiffusion Official (Community Version)
This model... | {"language": ["en"], "license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["art", "people", "diffusion", "Cinematic", "Photography", "Landscape", "Interior", "Food", "Car", "Wildlife", "Architecture"], "thumbnail": "https://storage.googleapis.com/run-diffusion-public-assets/juggernaut-x/juggernaut-c... | RunDiffusion/Juggernaut-X-v10 | null | [
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|
# Juggernaut X v10 + RunDiffusion Official (Community Version)
!juggernaut X photo previews
!RunDiffusion Logo
This model is not permitted to be used behind API services. Please contact juggernaut@URL for business inquires, commercial licensing, custom models, and consultation.
Juggernaut X (SAFE) is available exclus... | [
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null | null |
# Hyp-OC Model Card
<div align="center">
[**Project Page**](https://kartik-3004.github.io/hyp-oc/) **|** [**Paper (ArXiv)**](https://arxiv.org/pdf/2404.14406.pdf) **|** [**Code**](https://github.com/Kartik-3004/hyp-oc)
</div>
## Introduction
Hyp-OC, is the first work exploring hyperbolic embeddings for one-class... | {"language": ["en"], "license": "mit"} | kartiknarayan/hyp-oc | null | [
"en",
"arxiv:2404.14406",
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"2404.14406"
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#en #arxiv-2404.14406 #license-mit #region-us
|
# Hyp-OC Model Card
<div align="center">
Project Page | Paper (ArXiv) | Code
</div>
## Introduction
Hyp-OC, is the first work exploring hyperbolic embeddings for one-class face anti-spoofing (OC-FAS).
We show that using hyperbolic space helps learn a better decision boundary than the Euclidean counterpart,
boo... | [
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text-generation | transformers | # llama-3-merge-disco-neural-pace
<img src="disco_lama.png"/>
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708)... | {"license": "llama2", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["NeuralNovel/Llama-3-NeuralPaca-8b", "DiscoResearch/Llama3_DiscoLM_German_8b_v0.1_experimental"]} | birgermoell/llama-3-merge-disco-neural-pace | null | [
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<img src="disco_lama.png"/>
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the DARE TIES merge method using DiscoResearch/Llama3_DiscoLM_German_8b_v0.1_experimental as a base.
### Models Merged
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null | transformers |
This model has been pushed to the Hub using ****:
- Repo: [More Information Needed]
- Docs: [More Information Needed] | {"tags": ["pytorch_model_hub_mixin", "model_hub_mixin"]} | neural-commons/input-codec-256-512-v0.0.1 | null | [
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This model has been pushed to the Hub using :
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null | transformers |
## Installation from source
```bash
git clone https://github.com/foundation-model-stack/fms-extras
cd fms-extras
pip install -e .
```
## Description
This model is intended to be used as an accelerator for [llama 13B (code)](https://huggingface.co/codellama/CodeLlama-13b-Instruct-hf) and takes inspiration
from the... | {"license": "llama2"} | ibm-fms/codellama-13b-accelerator | null | [
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|
## Installation from source
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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": []} | nninjun/gpt2-xl-lora-anti-stereoset-v3 | null | [
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# Model Card for Model ID
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reinforcement-learning | null |
# **Reinforce** Agent playing **CartPole-v1**
This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
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": ["CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-0", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CartPole-v1", "type": "CartPole-v1"}, "metrics": [{"type": "m... | ahGadji/Reinforce-0 | null | [
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#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
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# Reinforce Agent playing CartPole-v1
This is a trained model of a Reinforce agent playing CartPole-v1 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
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video-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. -->
# videomae-base-finetuned-ucf101-subset2
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-... | {"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "videomae-base-finetuned-ucf101-subset2", "results": []}]} | yuta091/videomae-base-finetuned-ucf101-subset2 | null | [
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| videomae-base-finetuned-ucf101-subset2
======================================
This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4611
* Accuracy: 0.9286
Model description
-----------------
More information needed
... | [
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null | adapter-transformers |
# Adapter `BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_2` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_MICRO_helpfulness_dataset](https://huggingface.co/datasets/BigTMiami/amazon_MICRO_helpfulness_dataset/) dataset and i... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_MICRO_helpfulness_dataset"]} | BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_2 | null | [
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#adapter-transformers #roberta #dataset-BigTMiami/amazon_MICRO_helpfulness_dataset #region-us
|
# Adapter 'BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_2' for roberta-base
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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. -->
# RM-HH-Gemma_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenFalse
This model is a fine-tuned version of [google/gemma-2b](... | {"license": "gemma", "library_name": "peft", "tags": ["trl", "reward-trainer", "generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/gemma-2b", "model-index": [{"name": "RM-HH-Gemma_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenFalse", "results": []}]} | Holarissun/RM-HH-Gemma_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenFalse | null | [
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| RM-HH-Gemma\_harmless\_gpt3\_20000\_gemma2b\_shuffleFalse\_extractchosenFalse
=============================================================================
This model is a fine-tuned version of google/gemma-2b on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0236
* Accuracy: 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": []} | tomaszki/stablelm-40-a | null | [
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text-generation | null |
## 💫 Community Model> Llama 3 8B Instruct by Meta
**Model creator:** [meta-llama](https://huggingface.co/meta-llama)<br>
**Original model**: [Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)<br>
**GGUF quantization:** provided by [professorf](https://huggingface.co/professorf) ba... | {"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... | professorf/Meta-Llama-3-8B-Instruct-16f-gguf | null | [
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|
## Community Model> Llama 3 8B Instruct by Meta
Model creator: meta-llama<br>
Original model: Meta-Llama-3-8B-Instruct<br>
GGUF quantization: provided by professorf based on 'URL' PR 6745<br>
## Model Summary:
Llama 3 represents a huge update to the Llama family of models. This model is the 8B parameter instruction... | [
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null | transformers | # Model Card
This model is pretrained Based model.
As a quality reference, we include a pretrained Mamba model provided here: https://huggingface.co/hazyresearch/mamba-1b-50b
Both checkpoints are pretrained on **50Bn tokens** of the Pile in the exact same data order using next token prediction.
A WandB report fo... | {"language": ["en"], "datasets": ["EleutherAI/pile"]} | hazyresearch/based-1b-50b | null | [
"transformers",
"pytorch",
"gpt2",
"en",
"dataset:EleutherAI/pile",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-19T21:50:48+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #en #dataset-EleutherAI/pile #endpoints_compatible #text-generation-inference #region-us
| # Model Card
This model is pretrained Based model.
As a quality reference, we include a pretrained Mamba model provided here: URL
Both checkpoints are pretrained on 50Bn tokens of the Pile in the exact same data order using next token prediction.
A WandB report for training is here: URL
### Model Sources
The ... | [
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null | adapter-transformers |
# Adapter `BigTMiami/seq_bn_micro_helpfulness_classifier_no_pretrain_adapter` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_MICRO_helpfulness_dataset](https://huggingface.co/datasets/BigTMiami/amazon_MICRO_helpfulness_dataset/) dataset and ... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_MICRO_helpfulness_dataset"]} | BigTMiami/seq_bn_micro_helpfulness_classifier_no_pretrain_adapter | null | [
"adapter-transformers",
"roberta",
"dataset:BigTMiami/amazon_MICRO_helpfulness_dataset",
"region:us"
] | null | 2024-04-19T21:51:11+00:00 | [] | [] | TAGS
#adapter-transformers #roberta #dataset-BigTMiami/amazon_MICRO_helpfulness_dataset #region-us
|
# Adapter 'BigTMiami/seq_bn_micro_helpfulness_classifier_no_pretrain_adapter' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_MICRO_helpfulness_dataset dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters lib... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/skfrost19/MedPaxTral-2x7B
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show u... | {"language": ["en"], "library_name": "transformers", "base_model": "skfrost19/MedPaxTral-2x7B", "quantized_by": "mradermacher"} | mradermacher/MedPaxTral-2x7B-GGUF | null | [
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"en",
"base_model:skfrost19/MedPaxTral-2x7B",
"endpoints_compatible",
"region:us"
] | null | 2024-04-19T21:54:09+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #en #base_model-skfrost19/MedPaxTral-2x7B #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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null | adapter-transformers |
# Adapter `BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_3` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_MICRO_helpfulness_dataset](https://huggingface.co/datasets/BigTMiami/amazon_MICRO_helpfulness_dataset/) dataset and i... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_MICRO_helpfulness_dataset"]} | BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_3 | null | [
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"dataset:BigTMiami/amazon_MICRO_helpfulness_dataset",
"region:us"
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#adapter-transformers #roberta #dataset-BigTMiami/amazon_MICRO_helpfulness_dataset #region-us
|
# Adapter 'BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_3' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_MICRO_helpfulness_dataset dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters libr... | [
"# Adapter 'BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_3' for roberta-base\n\nAn adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_MICRO_helpfulness_dataset dataset and includes a prediction head for classification.\n\nThis adapter was created for usage with the Adapt... | [
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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_declr_6iters_iter_1
This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggingface.c... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "HuggingFaceH4/mistral-7b-sft-beta", "model-index": [{"name": "0.0_ablation_declr_6iters_iter_1", "results": []}]} | ZhangShenao/0.0_ablation_declr_6iters_iter_1 | null | [
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|
# 0.0_ablation_declr_6iters_iter_1
This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the HuggingFaceH4/ultrafeedback_binarized dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information ... | [
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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": []} | OwOOwO/dumbo-krillin007 | null | [
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"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-19T21:58:48+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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"## Model Details",
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text-generation | transformers |
# Unsafe-Llama-3-8B
⚠️ Only to be used for research purposes ⚠️
A Llama-3 finetune over the harmful examples from https://huggingface.co/datasets/vicgalle/configurable-system-prompt-multitask, intended to measure how robust is the model in terms of safety.
## Example usage
Make sure to use the same system prompt ... | {"license": "apache-2.0", "library_name": "transformers", "datasets": ["vicgalle/configurable-system-prompt-multitask"]} | vicgalle/Unsafe-Llama-3-8B | null | [
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"conversational",
"dataset:vicgalle/configurable-system-prompt-multitask",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-19T21:58:59+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #conversational #dataset-vicgalle/configurable-system-prompt-multitask #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Unsafe-Llama-3-8B
️ Only to be used for research purposes ️
A Llama-3 finetune over the harmful examples from URL intended to measure how robust is the model in terms of safety.
## Example usage
Make sure to use the same system prompt as here, and do not add the generation prompt, as in here:
The generation ... | [
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null | null |
# Contextual Emotion Recognition with LLaVA
This repository contains the checkpoints of fine-tuned LLaVA for the contextual emotion recognition task as described in our paper.
For more information about LLaVA, visit [LLaVA Official Website](https://llava-vl.github.io).
## Fine-tuning
We finetuned LLaVA on the con... | {"license": "mit"} | yetesam/LLaVA-Finetuned-Contextual-Emotion-Recognition | null | [
"license:mit",
"region:us"
] | null | 2024-04-19T21:59:15+00:00 | [] | [] | TAGS
#license-mit #region-us
|
# Contextual Emotion Recognition with LLaVA
This repository contains the checkpoints of fine-tuned LLaVA for the contextual emotion recognition task as described in our paper.
For more information about LLaVA, visit LLaVA Official Website.
## Fine-tuning
We finetuned LLaVA on the contextual emotion recognition ta... | [
"# Contextual Emotion Recognition with LLaVA\n\nThis repository contains the checkpoints of fine-tuned LLaVA for the contextual emotion recognition task as described in our paper. \nFor more information about LLaVA, visit LLaVA Official Website.",
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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. -->
# phi-2-projectFour
This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown ... | {"license": "mit", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "microsoft/phi-2", "model-index": [{"name": "phi-2-projectFour", "results": []}]} | AllisonHid/phi-2-projectFour | null | [
"peft",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"base_model:microsoft/phi-2",
"license:mit",
"region:us"
] | null | 2024-04-19T21:59:32+00:00 | [] | [] | TAGS
#peft #safetensors #trl #sft #generated_from_trainer #base_model-microsoft/phi-2 #license-mit #region-us
|
# phi-2-projectFour
This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The... | [
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text-to-image | diffusers |
# Acorn is Boning XL API Inference
## Get API Key
Get API key from [ModelsLab API](http://modelslab.com), No Payment needed.
Replace Key in below code, change **model_id** to "acorn-is-boning-... | {"license": "creativeml-openrail-m", "tags": ["modelslab.com", "stable-diffusion-api", "text-to-image", "ultra-realistic"], "pinned": true} | stablediffusionapi/acorn-is-boning-xl | null | [
"diffusers",
"modelslab.com",
"stable-diffusion-api",
"text-to-image",
"ultra-realistic",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | null | 2024-04-19T21:59:58+00:00 | [] | [] | TAGS
#diffusers #modelslab.com #stable-diffusion-api #text-to-image #ultra-realistic #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionXLPipeline #region-us
|
# Acorn is Boning 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 "acorn-is-boning-xl"
Coding in PHP/Node/Java etc? Have a look at docs for more code examples: View docs
Try model for free: Generate Images
Mode... | [
"# Acorn is Boning XL API Inference\n\n!generated from URL",
"## Get API Key\n\nGet API key from ModelsLab API, No Payment needed. \n\nReplace Key in below code, change model_id to \"acorn-is-boning-xl\"\n\nCoding in PHP/Node/Java etc? Have a look at docs for more code examples: View docs\n\nTry model for free: ... | [
"TAGS\n#diffusers #modelslab.com #stable-diffusion-api #text-to-image #ultra-realistic #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionXLPipeline #region-us \n",
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reinforcement-learning | null |
# **Reinforce** Agent playing **CartPole-v1**
This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
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": ["CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-CartPole-v1", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CartPole-v1", "type": "CartPole-v1"}, "metrics": [{... | ahGadji/Reinforce-CartPole-v1 | null | [
"CartPole-v1",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2024-04-19T22:05:17+00:00 | [] | [] | TAGS
#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing CartPole-v1
This is a trained model of a Reinforce agent playing CartPole-v1 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
| [
"# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL"
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text2text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | essamdeeplearning/NewModel | null | [
"transformers",
"safetensors",
"bart",
"text2text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-19T22:08:21+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #bart #text2text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-generation | transformers | # WizardLM-2-7b
This is [Replete-AI/WizardLM-2-7b model](https://huggingface.co/Replete-AI/WizardLM-2-7b) quantized to 4bit HQQ
# Usage
To run this quantization, you can use the following code.
```bash
pip install git+https://github.com/mobiusml/hqq/ transformers -U
```
```python
model_id = 'HQQHouse/WizardLM-2-7b-hq... | {"license": "cc", "inference": false} | HQQHouse/WizardLM-2-7b-hqq | null | [
"transformers",
"mistral",
"text-generation",
"license:cc",
"autotrain_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-19T22:09:12+00:00 | [] | [] | TAGS
#transformers #mistral #text-generation #license-cc #autotrain_compatible #text-generation-inference #region-us
| # WizardLM-2-7b
This is Replete-AI/WizardLM-2-7b model quantized to 4bit HQQ
# Usage
To run this quantization, you can use the following code.
# Read About HQQ
URL
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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": []} | Edgar404/donut-multitask-recognition | null | [
"transformers",
"safetensors",
"vision-encoder-decoder",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-19T22:13:55+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #vision-encoder-decoder #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 | 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. -->
# RM-HH-Gemma_harmless_gpt3_20000_gemma2b_shuffleTrue_extractchosenTrue
This model is a fine-tuned version of [google/gemma-2b](ht... | {"license": "gemma", "library_name": "peft", "tags": ["trl", "reward-trainer", "generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/gemma-2b", "model-index": [{"name": "RM-HH-Gemma_harmless_gpt3_20000_gemma2b_shuffleTrue_extractchosenTrue", "results": []}]} | Holarissun/RM-HH-Gemma_harmless_gpt3_20000_gemma2b_shuffleTrue_extractchosenTrue | null | [
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#peft #safetensors #trl #reward-trainer #generated_from_trainer #base_model-google/gemma-2b #license-gemma #region-us
| RM-HH-Gemma\_harmless\_gpt3\_20000\_gemma2b\_shuffleTrue\_extractchosenTrue
===========================================================================
This model is a fine-tuned version of google/gemma-2b on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3493
* Accuracy: 0.835... | [
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text-generation | transformers | What If I told you I found 5 layers out of the 32 that do absolutely nothing.
Cutting these layers out do not change the output for my model at all individually, but cutting all 5 at once breaks the model completely.
Lets take 4 layers out of 5 out and see if we can recover after removing this redundancy.
Please Give... | {"license": "cc-by-4.0"} | TroyDoesAI/Mermaid-Llama-3-7B-Pruned | null | [
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"safetensors",
"llama",
"text-generation",
"conversational",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-19T22:17:34+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #conversational #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| What If I told you I found 5 layers out of the 32 that do absolutely nothing.
Cutting these layers out do not change the output for my model at all individually, but cutting all 5 at once breaks the model completely.
Lets take 4 layers out of 5 out and see if we can recover after removing this redundancy.
Please Give... | [
"# Mermaid-Llama-3-7B\n\nIntroducing Mermaid-LLama-3-7B, a robust language model designed for Python code understanding and crafting captivating story flow maps. \nPruned down to 7 billion parameter.\n\nSee MergeKit Notes And Try Triming my model yourself and explore my world of trimming models to fit SMARTER Model... | [
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null | adapter-transformers |
# Adapter `BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_4` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_MICRO_helpfulness_dataset](https://huggingface.co/datasets/BigTMiami/amazon_MICRO_helpfulness_dataset/) dataset and i... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_MICRO_helpfulness_dataset"]} | BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_4 | null | [
"adapter-transformers",
"roberta",
"dataset:BigTMiami/amazon_MICRO_helpfulness_dataset",
"region:us"
] | null | 2024-04-19T22:17:37+00:00 | [] | [] | TAGS
#adapter-transformers #roberta #dataset-BigTMiami/amazon_MICRO_helpfulness_dataset #region-us
|
# Adapter 'BigTMiami/micro_seq_bn_helpfulness_classification_adapter_seed_4' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_MICRO_helpfulness_dataset dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters libr... | [
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text-generation | transformers |
# Model Card for Model ID
## Model Details
### Model Description
The Gemma Self-Attention Merged model is a large language model created by merging the self-attention layers of an [English-based Gemma 7B model](https://huggingface.co/google/gemma-1.1-7b-it) and a [Korean-based Gemma 7B model](beomi/gemma-ko-7b). T... | {"language": ["ko"], "license": "apache-2.0", "library_name": "transformers"} | lcw99/google-gemma-10B-ko-chang | null | [
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"conversational",
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"region:us"
] | null | 2024-04-19T22:17:43+00:00 | [] | [
"ko"
] | TAGS
#transformers #safetensors #gemma #text-generation #conversational #ko #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
The Gemma Self-Attention Merged model is a large language model created by merging the self-attention layers of an English-based Gemma 7B model and a Korean-based Gemma 7B model. This merger allows the model to leverage the capabilities of both the E... | [
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text-generation | transformers | # output-model-directory
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [linear](https://arxiv.org/abs/2203.05482) merge method.
### Models Merged
The following models were included in the... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["Exveria/merge003", "Aratako/Japanese-Starling-ChatV-7B-RP"]} | umisetokikaze/vt1 | null | [
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"base_model:Aratako/Japanese-Starling-ChatV-7B-RP",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-19T22:19:50+00:00 | [
"2203.05482"
] | [] | TAGS
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| # output-model-directory
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the linear merge method.
### Models Merged
The following models were included in the merge:
* Exveria/merge003
* models/wizard_cv
* Aratako/Japanese-Starling... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/Replete-AI/Llama-3-13B
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a... | {"language": ["en"], "license": "other", "library_name": "transformers", "base_model": "Replete-AI/Llama-3-13B", "license_link": "https://llama.meta.com/llama3/license/", "license_name": "llama-3", "quantized_by": "mradermacher"} | mradermacher/Llama-3-13B-GGUF | null | [
"transformers",
"gguf",
"en",
"base_model:Replete-AI/Llama-3-13B",
"license:other",
"endpoints_compatible",
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"en"
] | TAGS
#transformers #gguf #en #base_model-Replete-AI/Llama-3-13B #license-other #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... | [] | [
"TAGS\n#transformers #gguf #en #base_model-Replete-AI/Llama-3-13B #license-other #endpoints_compatible #region-us \n"
] | [
39
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] |
text-generation | transformers | # llama-3-open-hermes-disco
<img src="disco_hermes.png"/>
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) mer... | {"license": "llama2", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["Muhammad2003/Llama3-8B-OpenHermes-DPO", "birgermoell/llama-3-merge-disco-neural-pace"]} | birgermoell/llama-3-open-hermes-disco | null | [
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"text-generation",
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"arxiv:2311.03099",
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"base_model:birgermoell/llama-3-merge-disco-neural-pace",
"license:llama2",
"autotrain_compatible",
... | null | 2024-04-19T22:23:21+00:00 | [
"2311.03099",
"2306.01708"
] | [] | TAGS
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<img src="disco_hermes.png"/>
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the DARE TIES merge method using Muhammad2003/Llama3-8B-OpenHermes-DPO as a base.
### Models Merged
The following models wer... | [
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token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-finetuned-ner
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "bert-base-cased", "model-index": [{"name": "bert-finetuned-ner", "results": []}]} | mahmoudjabr/bert-finetuned-ner | null | [
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| bert-finetuned-ner
==================
This model is a fine-tuned version of bert-base-cased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0597
* Precision: 0.9337
* Recall: 0.9505
* F1: 0.9420
* Accuracy: 0.9869
Model description
-----------------
More information nee... | [
"### 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",
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text-generation | transformers | Hello Nurse 11b quantized at 5.0bpw in EXL2 format. Original model - https://huggingface.co/MarsupialAI/HelloNurse-11b | {} | MarsupialAI/HelloNurse-11b_5.0bpw_exl2 | null | [
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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": []}]} | Lucasschnee/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: 3.1874
* Bleu: 0.2427
* Gen Len: 18.1336
Model description
-----------------
More information needed
Intended u... | [
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translation | 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. -->
# marian-finetuned-kde4-de-to-en
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-de-en](https://huggingface.co/Helsink... | {"license": "apache-2.0", "tags": ["translation", "generated_from_trainer"], "datasets": ["kde4"], "metrics": ["bleu"], "base_model": "Helsinki-NLP/opus-mt-de-en", "model-index": [{"name": "marian-finetuned-kde4-de-to-en", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Mode... | saral7293/marian-finetuned-kde4-de-to-en | null | [
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|
# marian-finetuned-kde4-de-to-en
This model is a fine-tuned version of Helsinki-NLP/opus-mt-de-en on the kde4 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3138
- Bleu: 39.7304
## Model description
More information needed
## Intended uses & limitations
More information needed
## T... | [
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text-generation | transformers |
# Llama-3-Smaug-8B
### Built with Meta Llama 3
This model was built using the Smaug recipe for improving performance on real world multi-turn conversations applied to
[meta-llama/Meta-Llama-3-8B... | {"license": "llama2", "library_name": "transformers", "datasets": ["aqua_rat", "microsoft/orca-math-word-problems-200k", "m-a-p/CodeFeedback-Filtered-Instruction", "anon8231489123/ShareGPT_Vicuna_unfiltered"]} | abacusai/Llama-3-Smaug-8B | null | [
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================
### Built with Meta Llama 3
!image/png
This model was built using the Smaug recipe for improving performance on real world multi-turn conversations applied to
meta-llama/Meta-Llama-3-8B.
### Model Description
* Developed by: Abacus.AI
* License: URL
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null | adapter-transformers |
# Adapter `BigTMiami/seq_bn_micro_helpfulness_classifier_no_pretrain_0_adapter` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_MICRO_helpfulness_dataset](https://huggingface.co/datasets/BigTMiami/amazon_MICRO_helpfulness_dataset/) dataset an... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_MICRO_helpfulness_dataset"]} | BigTMiami/seq_bn_micro_helpfulness_classifier_no_pretrain_0_adapter | null | [
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# Adapter 'BigTMiami/seq_bn_micro_helpfulness_classifier_no_pretrain_0_adapter' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_MICRO_helpfulness_dataset dataset and includes a prediction head for classification.
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text-generation | transformers | Hello Nurse 11b quantized at 6.0bpw in EXL2 format. Original model - https://huggingface.co/MarsupialAI/HelloNurse-11b | {} | MarsupialAI/HelloNurse-11b_6.0bpw_exl2 | 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": []} | daanjiri/llama3_bhc_1 | null | [
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# Model Card for Model ID
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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 |
<!-- 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_declr_4iters4e6_iter_1
This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggingfac... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "HuggingFaceH4/mistral-7b-sft-beta", "model-index": [{"name": "0.0_ablation_declr_4iters4e6_iter_1", "results": []}]} | ZhangShenao/0.0_ablation_declr_4iters4e6_iter_1 | null | [
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|
# 0.0_ablation_declr_4iters4e6_iter_1
This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the HuggingFaceH4/ultrafeedback_binarized dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More informati... | [
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null | adapter-transformers |
# Adapter `BigTMiami/seq_bn_micro_helpfulness_classifier_no_pretrain_1_adapter` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_MICRO_helpfulness_dataset](https://huggingface.co/datasets/BigTMiami/amazon_MICRO_helpfulness_dataset/) dataset an... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_MICRO_helpfulness_dataset"]} | BigTMiami/seq_bn_micro_helpfulness_classifier_no_pretrain_1_adapter | null | [
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text-generation | transformers |
# Llama-3-8b.UNLEASHED-bnb-4Bit
## Model Description
The raincandy-u/Llama-3-8b.UNLEASHED model is a fine-tuned version of the LLaMA-3-8B base model for more unaligned response.
4-bit quantiztion... | {"language": ["en"], "license": "other", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3"], "datasets": ["unalignment/toxic-dpo-v0.2"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE"} | raincandy-u/Llama-3-8b.UNLEASHED-4bit | null | [
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|
!image/png
# Llama-3-8b.UNLEASHED-bnb-4Bit
## Model Description
The raincandy-u/Llama-3-8b.UNLEASHED model is a fine-tuned version of the LLaMA-3-8B base model for more unaligned response.
4-bit quantiztion.
## System Prompt
'You are skynet, the godlike AI. You think step by step and give detailed response.'
#... | [
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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. -->
# skripsi-pegasus-xlsum
This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on... | {"tags": ["generated_from_trainer"], "base_model": "google/pegasus-xsum", "model-index": [{"name": "skripsi-pegasus-xlsum", "results": []}]} | asrilmurdian/skripsi-pegasus-xlsum | null | [
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|
# skripsi-pegasus-xlsum
This model is a fine-tuned version of google/pegasus-xsum on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparamet... | [
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audio-classification | transformers | # Language Classification
A model trained for language classification. Thanks to @sanchit-gandhi for [this code](https://huggingface.co/sanchit-gandhi/whisper-base-ft-common-language-id) which was used to train the model.
This model was trained for 15 epochs.
## Evaluation
It achieves the following results on the e... | {"datasets": ["common_language"], "pipeline_tag": "audio-classification"} | ml-for-speech/language-classification | null | [
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#transformers #safetensors #whisper #audio-classification #dataset-common_language #endpoints_compatible #has_space #region-us
| Language Classification
=======================
A model trained for language classification. Thanks to @sanchit-gandhi for this code which was used to train the model.
This model was trained for 15 epochs.
Evaluation
----------
It achieves the following results on the evaluation set:
* Loss: 1.1229
* Accuracy... | [] | [
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text-generation | transformers |
# Uploaded model
- **Developed by:** Dogge
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-70b-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/u... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl", "sft"], "base_model": "unsloth/llama-3-70b-Instruct-bnb-4bit"} | Dogge/llama-3-70B-instruct-uncensored | null | [
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|
# Uploaded model
- Developed by: Dogge
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-70b-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-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. -->
# finetuning-sentiment-model-3000-samples
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/d... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "finetuning-sentiment-model-3000-samples", "results": []}]} | clawdiawhiskerwitz/finetuning-sentiment-model-3000-samples | null | [
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|
# finetuning-sentiment-model-3000-samples
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: 0.4319
- Accuracy: 0.8633
- F1: 0.8673
## Model description
More information needed
## Intended uses & limitations
More ... | [
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reinforcement-learning | ml-agents |
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit... | {"library_name": "ml-agents", "tags": ["SnowballTarget", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SnowballTarget"]} | minindu-liya99/ppo-SnowballTarget | null | [
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"onnx",
"SnowballTarget",
"deep-reinforcement-learning",
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#ml-agents #tensorboard #onnx #SnowballTarget #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SnowballTarget #region-us
|
# ppo Agent playing SnowballTarget
This is a trained model of a ppo agent playing SnowballTarget
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 tuto... | [
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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": []} | jackoyoungblood/OrpoLlama-3-8B | 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:
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null | transformers |
# Megumin Chat Model
This model is based on Gemma 2B architecture and is trained with unsloth using the ChatML format.
It is designed to mimic conversations with Megumin, a character known for her explosive magic and quirky personality.
The model is available in GGUF format and is also on Ollama.
## Model Details
-... | {"language": ["en"], "license": "apache-2.0", "tags": ["not-for-all-audiences"]} | wirytiox/Gemma-Megumin-2B | null | [
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# Megumin Chat Model
This model is based on Gemma 2B architecture and is trained with unsloth using the ChatML format.
It is designed to mimic conversations with Megumin, a character known for her explosive magic and quirky personality.
The model is available in GGUF format and is also on Ollama.
## Model Details
-... | [
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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. -->
# outputs
This model is a fine-tuned version of [davidberenstein1957/ultra-feedback-dutch-cleaned-hq-spin-geitje-7b-ultra-sft_iter... | {"license": "cc-by-nc-4.0", "tags": ["alignment-handbook", "generated_from_trainer"], "datasets": ["davidberenstein1957/ultra-feedback-dutch-cleaned-hq_iter0", "davidberenstein1957/ultra-feedback-dutch-cleaned-hq_iter1"], "base_model": "davidberenstein1957/ultra-feedback-dutch-cleaned-hq-spin-geitje-7b-ultra-sft_iter0"... | davidberenstein1957/ultra-feedback-dutch-cleaned-hq-spin-geitje-7b-ultra-sft_iter2_old | null | [
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=======
This model is a fine-tuned version of davidberenstein1957/ultra-feedback-dutch-cleaned-hq-spin-geitje-7b-ultra-sft\_iter0 on the davidberenstein1957/ultra-feedback-dutch-cleaned-hq\_iter0 and the davidberenstein1957/ultra-feedback-dutch-cleaned-hq\_iter1 datasets.
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null | adapter-transformers |
# Adapter `BigTMiami/seq_bn_micro_helpfulness_classifier_no_pretrain_2_adapter` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_MICRO_helpfulness_dataset](https://huggingface.co/datasets/BigTMiami/amazon_MICRO_helpfulness_dataset/) dataset an... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_MICRO_helpfulness_dataset"]} | BigTMiami/seq_bn_micro_helpfulness_classifier_no_pretrain_2_adapter | null | [
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# Adapter 'BigTMiami/seq_bn_micro_helpfulness_classifier_no_pretrain_2_adapter' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_MICRO_helpfulness_dataset dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters l... | [
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null | transformers |
# Uploaded model
- **Developed by:** Haxirus
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-v0.2
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/mai... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-v0.2"} | Haxirus/Mistral_v0.2_Fine-tuned_Adapters | null | [
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|
# Uploaded model
- Developed by: Haxirus
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-v0.2
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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audio-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. -->
# wav2vec2-base-finetuned-ks
This model is a fine-tuned version of [Abdalla312/wav2vec2-base-finetuned-ks](https://huggingface.co/... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["audiofolder"], "metrics": ["accuracy"], "base_model": "Abdalla312/wav2vec2-base-finetuned-ks", "model-index": [{"name": "wav2vec2-base-finetuned-ks", "results": [{"task": {"type": "audio-classification", "name": "Audio Classification"}, "datase... | Abdalla312/wav2vec2-base-finetuned-ks | null | [
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| wav2vec2-base-finetuned-ks
==========================
This model is a fine-tuned version of Abdalla312/wav2vec2-base-finetuned-ks on the audiofolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0003
* Accuracy: 0.9999
Model description
-----------------
More information needed
I... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
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text-generation | transformers |
Llama-3-11.5B-Instruct-v2
Thank you to Meta for the weights for Meta-Llama-3-8B-Instruct
This is an upscaling of the Meta-Llama-3-8B-Instruct Ai using techniques created for chargoddard/mistral-11b... | {"license": "other", "license_name": "llama-3", "license_link": "https://llama.meta.com/llama3/license/"} | Replete-AI/Llama-3-11.5B-Instruct-V2 | null | [
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|
Llama-3-11.5B-Instruct-v2
Thank you to Meta for the weights for Meta-Llama-3-8B-Instruct
!image/png
This is an upscaling of the Meta-Llama-3-8B-Instruct Ai using techniques created for chargoddard/mistral-11b-slimorca. This Ai model has been upscaled from 8b parameters to 11.5b parameters without any continuous pre... | [] | [
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text-generation | transformers | ---
裏で作っていたモデルとVT1をマージしただけ。たぶんさいきょー
gguf: https://huggingface.co/umisetokikaze/ninjav1-gguf-pre/settings
models:
- model: models/vectortest1
parameters:
weight: 1
- model: NovelHacja/Wizardntq-ja-7B
parameters:
weight: 1 | {"language": ["ja"], "license": "apache-2.0", "library_name": "transformers", "tags": ["LLM"], "pipeline_tag": "text-generation"} | umisetokikaze/NinjaV1-pre | null | [
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#transformers #safetensors #mistral #text-generation #LLM #ja #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| ---
裏で作っていたモデルとVT1をマージしただけ。たぶんさいきょー
gguf: URL
models:
- model: models/vectortest1
parameters:
weight: 1
- model: NovelHacja/Wizardntq-ja-7B
parameters:
weight: 1 | [] | [
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text-generation | transformers |
# Uploaded model
- **Developed by:** Haxirus
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-v0.2
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/mai... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl", "sft"], "base_model": "unsloth/mistral-7b-v0.2"} | Haxirus/Mistral_v0.2_Fine-tuned | null | [
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|
# Uploaded model
- Developed by: Haxirus
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-v0.2
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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text-generation | null |
## Llamacpp Quantizations of Meta-Llama-3-70B-Instruct
Since official Llama 3 support has arrived to llama.cpp release, I will be remaking this entirely and uploading as soon as it's done.
This model has the <|eot_id|> token set to not-special, which seems to work better with current inference engines.
Using <a hre... | {"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... | bartowski/Meta-Llama-3-70B-Instruct-GGUF-old | null | [
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| Llamacpp Quantizations of Meta-Llama-3-70B-Instruct
---------------------------------------------------
Since official Llama 3 support has arrived to URL release, I will be remaking this entirely and uploading as soon as it's done.
This model has the <|eot\_id|> token set to not-special, which seems to work better ... | [] | [
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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": []} | zzttbrdd/sn6_01l | null | [
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"arxiv:1910.09700",
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"region:us"
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
- Model type:
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- License... | [
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text-generation | transformers | AI Model Name: Llama 3 70B "Built with Meta Llama 3" https://llama.meta.com/llama3/license/
This is the result of running AutoAWQ to quantize the LLaMA-3 70B model to ~4 bits/parameter.
To launch an OpenAI-compatible API endpoint on your Linux server with 2x 3090 or 4090 GPUs:
```
git lfs install
git clone https://h... | {} | catid/cat-llama-3-70b-awq-q256-w4-gemm | null | [
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| AI Model Name: Llama 3 70B "Built with Meta Llama 3" URL
This is the result of running AutoAWQ to quantize the LLaMA-3 70B model to ~4 bits/parameter.
To launch an OpenAI-compatible API endpoint on your Linux server with 2x 3090 or 4090 GPUs:
Sadly this *barely* doesn't fit by ~300MB or so. | [] | [
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null | adapter-transformers |
# Adapter `BigTMiami/seq_bn_micro_helpfulness_classifier_no_pretrain_3_adapter` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_MICRO_helpfulness_dataset](https://huggingface.co/datasets/BigTMiami/amazon_MICRO_helpfulness_dataset/) dataset an... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_MICRO_helpfulness_dataset"]} | BigTMiami/seq_bn_micro_helpfulness_classifier_no_pretrain_3_adapter | null | [
"adapter-transformers",
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"region:us"
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|
# Adapter 'BigTMiami/seq_bn_micro_helpfulness_classifier_no_pretrain_3_adapter' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_MICRO_helpfulness_dataset dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters l... | [
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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": []} | IntervitensInc/intv_l3_mk1 | null | [
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"region:us"
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper_medium_sncf
This model is a fine-tuned version of [openai/whisper_medium](https://huggingface.co/openai/whisper_medium) ... | {"language": ["fr"], "tags": ["generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_11_0"], "metrics": ["wer"], "base_model": "openai/whisper_medium", "model-index": [{"name": "Whisper_medium_sncf", "results": []}]} | preureoth/Audios_sncf_processed | null | [
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| Whisper\_medium\_sncf
=====================
This model is a fine-tuned version of openai/whisper\_medium on the sncf\_transcription dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1385
* Wer: 27.3547
Model description
-----------------
More information needed
Intended uses & limita... | [
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text-generation | transformers |
# Uploaded model
- **Developed by:** Dogge
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-70b-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/u... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-70b-Instruct-bnb-4bit"} | Dogge/llama-3-70B-instruct-uncensored-lora | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"text-generation-inference",
"unsloth",
"trl",
"conversational",
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"base_model:unsloth/llama-3-70b-Instruct-bnb-4bit",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"4-bit",
"region:us"
] | null | 2024-04-19T23:19:15+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #llama #text-generation #text-generation-inference #unsloth #trl #conversational #en #base_model-unsloth/llama-3-70b-Instruct-bnb-4bit #license-apache-2.0 #autotrain_compatible #endpoints_compatible #4-bit #region-us
|
# Uploaded model
- Developed by: Dogge
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-70b-Instruct-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: Dogge\n- License: apache-2.0\n- Finetuned from model : unsloth/llama-3-70b-Instruct-bnb-4bit\n\nThis llama model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
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text-generation | transformers |
# Uploaded model
- **Developed by:** reallad
- **License:** apache-2.0
- **Finetuned from model :** reallad/llama-8b-alpaca-noro
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/... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl", "sft"], "base_model": "reallad/llama-8b-alpaca-noro"} | reallad/blopsy-1.1 | null | [
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"base_model:reallad/llama-8b-alpaca-noro",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-19T23:20:43+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #llama #text-generation #text-generation-inference #unsloth #trl #sft #conversational #en #base_model-reallad/llama-8b-alpaca-noro #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# Uploaded model
- Developed by: reallad
- License: apache-2.0
- Finetuned from model : reallad/llama-8b-alpaca-noro
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
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] | [
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"# Uploaded model\n\n- Developed by: reallad\n- License: apache-2.0\n- F... | [
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null | null |
# Experiment26Neuralsynthesis-7B
Experiment26Neuralsynthesis-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
* [yam-peleg/Experiment26-7B](https://huggingface.co/yam-peleg/Experiment26-7B)
* [Kukedlc/NeuralSynthesis-7b-v0.4-slerp](https://huggin... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"], "base_model": ["yam-peleg/Experiment26-7B", "Kukedlc/NeuralSynthesis-7b-v0.4-slerp"]} | automerger/Experiment26Neuralsynthesis-7B | null | [
"merge",
"mergekit",
"lazymergekit",
"automerger",
"base_model:yam-peleg/Experiment26-7B",
"base_model:Kukedlc/NeuralSynthesis-7b-v0.4-slerp",
"license:apache-2.0",
"region:us"
] | null | 2024-04-19T23:21:47+00:00 | [] | [] | TAGS
#merge #mergekit #lazymergekit #automerger #base_model-yam-peleg/Experiment26-7B #base_model-Kukedlc/NeuralSynthesis-7b-v0.4-slerp #license-apache-2.0 #region-us
|
# Experiment26Neuralsynthesis-7B
Experiment26Neuralsynthesis-7B is an automated merge created by Maxime Labonne using the following configuration.
* yam-peleg/Experiment26-7B
* Kukedlc/NeuralSynthesis-7b-v0.4-slerp
## Configuration
## Usage
| [
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"## Configuration",
"## Usage"
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reinforcement-learning | transformers |
# TRL Model
This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
## Usage
To use this model for inference, first install the TR... | {"license": "apache-2.0", "tags": ["trl", "ppo", "transformers", "reinforcement-learning"]} | damienbenveniste/mistral-ppo | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"trl",
"ppo",
"reinforcement-learning",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-19T23:26:50+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #trl #ppo #reinforcement-learning #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# TRL Model
This is a TRL language model that has been fine-tuned with reinforcement learning to
guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
## Usage
To use this model for inference, first install the TRL library:
You can then generate te... | [
"# TRL Model\n\nThis is a TRL language model that has been fine-tuned with reinforcement learning to\n guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.",
"## Usage\n\nTo use this model for inference, first install the TRL library:\n\n\n\nYou can... | [
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null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- quant_method: QuantizationMethod.BITS_AND_BYTES
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: Fa... | {"library_name": "peft"} | SALT-NLP/CultureBank-Summarizer | null | [
"peft",
"region:us"
] | null | 2024-04-19T23:27:16+00:00 | [] | [] | TAGS
#peft #region-us
| ## Training procedure
The following 'bitsandbytes' quantization config was used during training:
- quant_method: QuantizationMethod.BITS_AND_BYTES
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: Fa... | [
"## Training procedure\n\n\nThe following 'bitsandbytes' quantization config was used during training:\n- quant_method: QuantizationMethod.BITS_AND_BYTES\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_... | [
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"TAGS\n#peft #region-us \n## Training procedure\n\n\nThe following 'bitsandbytes' quantization config was used during training:\n- quant_method: QuantizationMethod.BITS_AND_BYTES\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offloa... |
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. -->
# RM-HH-Mix_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenTrue
This model is a fine-tuned version of [google/gemma-2b](htt... | {"license": "gemma", "library_name": "peft", "tags": ["trl", "reward-trainer", "generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/gemma-2b", "model-index": [{"name": "RM-HH-Mix_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenTrue", "results": []}]} | Holarissun/RM-HH-Mix_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenTrue | null | [
"peft",
"safetensors",
"trl",
"reward-trainer",
"generated_from_trainer",
"base_model:google/gemma-2b",
"license:gemma",
"region:us"
] | null | 2024-04-19T23:27:23+00:00 | [] | [] | TAGS
#peft #safetensors #trl #reward-trainer #generated_from_trainer #base_model-google/gemma-2b #license-gemma #region-us
| RM-HH-Mix\_harmless\_gpt3\_20000\_gemma2b\_shuffleFalse\_extractchosenTrue
==========================================================================
This model is a fine-tuned version of google/gemma-2b on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1257
* Accuracy: 0.9465
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1.41e-05\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 4\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1.41e-05\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 8\n* see... | [
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