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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. -->
# GUE_EMP_H3K79me3-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_EMP_H3K79me3-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K79me3-seqsight_16384_512_22M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_EMP\_H3K79me3-seqsight\_16384\_512\_22M-L1\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_EMP\_H3K79me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4510
* F1 Sc... | [
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - embracellm/sushi_LoRA_2
<Gallery />
## Model description
These are embracellm/sushi_LoRA_2 LoR... | {"license": "openrail++", "library_name": "diffusers", "tags": ["text-to-image", "text-to-image", "diffusers-training", "diffusers", "dora", "template:sd-lora", "stable-diffusion-xl", "stable-diffusion-xl-diffusers"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "a photo of sushi", "widg... | embracellm/sushi_LoRA_2 | null | [
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|
# SDXL LoRA DreamBooth - embracellm/sushi_LoRA_2
<Gallery />
## Model description
These are embracellm/sushi_LoRA_2 LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using DreamBooth.
LoRA for the text encoder was enabled: False.
Special VAE used for training: madeb... | [
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text-generation | transformers |
# stablelm-2-zephyr-1.6b-slerpx2
stablelm-2-zephyr-1.6b-slerpx2 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [aipib/stablelm-2-1_6b_slerpmerge](https://huggingface.co/aipib/stablelm-2-1_6b_slerpmerge)
* [stabilityai/s... | {"tags": ["merge", "mergekit", "lazymergekit", "aipib/stablelm-2-1_6b_slerpmerge", "stabilityai/stablelm-2-1_6b"], "base_model": ["aipib/stablelm-2-1_6b_slerpmerge", "stabilityai/stablelm-2-1_6b"]} | aipib/stablelm-2-zephyr-1.6b-slerpx2 | null | [
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|
# stablelm-2-zephyr-1.6b-slerpx2
stablelm-2-zephyr-1.6b-slerpx2 is a merge of the following models using LazyMergekit:
* aipib/stablelm-2-1_6b_slerpmerge
* stabilityai/stablelm-2-1_6b
## Configuration
## Usage
| [
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 0.001_5iters_bs256_nodpo_only4w_iter_1
This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://hugging... | {"license": "mit", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "HuggingFaceH4/mistral-7b-sft-beta", "model-index": [{"name": "0.001_5iters_bs256_nodpo_only4w_iter_1", "results": []}]} | ShenaoZhang/0.001_5iters_bs256_nodpo_only4w_iter_1 | null | [
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"endpoints_compatible... | null | 2024-04-27T08:13:33+00:00 | [] | [] | TAGS
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|
# 0.001_5iters_bs256_nodpo_only4w_iter_1
This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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# 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 | null |
# EnverLee/DAVinCI-42dot_LLM-PLM-1.3B-v1.2-Q4_0-GGUF
This model was converted to GGUF format from [`jungyuko/DAVinCI-42dot_LLM-PLM-1.3B-v1.2`](https://huggingface.co/jungyuko/DAVinCI-42dot_LLM-PLM-1.3B-v1.2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Re... | {"license": "cc-by-nc-4.0", "tags": ["llama-cpp", "gguf-my-repo"]} | EnverLee/DAVinCI-42dot_LLM-PLM-1.3B-v1.2-Q4_0-GGUF | null | [
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"llama-cpp",
"gguf-my-repo",
"license:cc-by-nc-4.0",
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#gguf #llama-cpp #gguf-my-repo #license-cc-by-nc-4.0 #region-us
|
# EnverLee/DAVinCI-42dot_LLM-PLM-1.3B-v1.2-Q4_0-GGUF
This model was converted to GGUF format from 'jungyuko/DAVinCI-42dot_LLM-PLM-1.3B-v1.2' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or ... | [
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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. -->
# GUE_EMP_H3K79me3-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_EMP_H3K79me3-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K79me3-seqsight_16384_512_22M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:16:16+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_EMP\_H3K79me3-seqsight\_16384\_512\_22M-L8\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_EMP\_H3K79me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4452
* F1 Sc... | [
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... | [
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null | transformers | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/Manavshah/llama4-dolphin-8B
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show... | {"language": ["en"], "library_name": "transformers", "base_model": "Manavshah/llama4-dolphin-8B", "quantized_by": "mradermacher"} | mradermacher/llama4-dolphin-8B-GGUF | null | [
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"endpoints_compatible",
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] | null | 2024-04-27T08:17:50+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #en #base_model-Manavshah/llama4-dolphin-8B #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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text-generation | transformers |
# stablelm-2-zephyr-1.6b-slerpx3
stablelm-2-zephyr-1.6b-slerpx3 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [aipib/stablelm-2-zephyr-1.6b-slerpx2](https://huggingface.co/aipib/stablelm-2-zephyr-1.6b-slerpx2)
* [aipib... | {"tags": ["merge", "mergekit", "lazymergekit", "aipib/stablelm-2-zephyr-1.6b-slerpx2", "aipib/stablelm-2-1_6b_slerpmerge"], "base_model": ["aipib/stablelm-2-zephyr-1.6b-slerpx2", "aipib/stablelm-2-1_6b_slerpmerge"]} | aipib/stablelm-2-zephyr-1.6b-slerpx3 | null | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
"aipib/stablelm-2-zephyr-1.6b-slerpx2",
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"conversational",
"base_model:aipib/stablelm-2-zephyr-1.6b-slerpx2",
"base_model:aipib/stablelm-2-1_6b_slerpmerge",
"... | null | 2024-04-27T08:19:52+00:00 | [] | [] | TAGS
#transformers #safetensors #stablelm #text-generation #merge #mergekit #lazymergekit #aipib/stablelm-2-zephyr-1.6b-slerpx2 #aipib/stablelm-2-1_6b_slerpmerge #conversational #base_model-aipib/stablelm-2-zephyr-1.6b-slerpx2 #base_model-aipib/stablelm-2-1_6b_slerpmerge #autotrain_compatible #endpoints_compatible #reg... |
# stablelm-2-zephyr-1.6b-slerpx3
stablelm-2-zephyr-1.6b-slerpx3 is a merge of the following models using LazyMergekit:
* aipib/stablelm-2-zephyr-1.6b-slerpx2
* aipib/stablelm-2-1_6b_slerpmerge
## Configuration
## Usage
| [
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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": []} | cmpktheo/Droid | null | [
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"1910.09700"
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#transformers #safetensors #gemma #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | null | # rakib72642/Face_Detection_Logic
# HuggingFace: https://huggingface.co/rakib72642/Face_Detection_Logic
# Setup Global API
sudo apt install iproute2 -y && sudo apt install wget -y && sudo apt install unzip -y && sudo apt install unzip -y && sudo apt install nvtop -y && sudo apt-get install git-all -y && sudo apt-get... | {} | rakib72642/Face_Detection_Logic | null | [
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#doi-10.57967/hf/2132 #region-us
| # rakib72642/Face_Detection_Logic
# HuggingFace: URL
# Setup Global API
sudo apt install iproute2 -y && sudo apt install wget -y && sudo apt install unzip -y && sudo apt install unzip -y && sudo apt install nvtop -y && sudo apt-get install git-all -y && sudo apt-get install git-lfs -y && sudo apt-get update && sudo ... | [
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unconditional-image-generation | diffusers | # 此模型是用于生成蝴蝶图像的无条件生成扩散模型 by shoe
'''python
from diffusers import DDPMPipeline
pipeline = DDPMPipeline.from_pretrained('{hub_model_id}')
image = pipeline().images[0]
image | {"language": ["en"], "license": "mit", "library_name": "diffusers", "tags": ["code"], "datasets": ["huggan/smithsonian_butterflies_subset"], "metrics": ["code_eval"], "targs": ["pytorch", "diffusers", "unconditional-image-generation", "diffusion-models-class"], "pipeline_tag": "unconditional-image-generation"} | shao918516/sd-class-butterflies-32 | null | [
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"en",
"dataset:huggan/smithsonian_butterflies_subset",
"license:mit",
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"region:us"
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"en"
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#diffusers #safetensors #code #unconditional-image-generation #en #dataset-huggan/smithsonian_butterflies_subset #license-mit #diffusers-DDPMPipeline #region-us
| # 此模型是用于生成蝴蝶图像的无条件生成扩散模型 by shoe
'''python
from diffusers import DDPMPipeline
pipeline = DDPMPipeline.from_pretrained('{hub_model_id}')
image = pipeline().images[0]
image | [
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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": []} | swj0419/hp_all_STEP0000010 | null | [
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"safetensors",
"llama",
"text-generation",
"arxiv:1910.09700",
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"text-generation-inference",
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"1910.09700"
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- 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. -->
# GUE_EMP_H3K79me3-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_EMP_H3K79me3-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K79me3-seqsight_16384_512_22M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:25:49+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_EMP\_H3K79me3-seqsight\_16384\_512\_22M-L32\_f
===================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_EMP\_H3K79me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4634
* F1 ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | transformers | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/CalderaAI/Hexoteric-7B
<!-- 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": "apache-2.0", "library_name": "transformers", "tags": ["mistral", "mix"], "base_model": "CalderaAI/Hexoteric-7B", "quantized_by": "mradermacher"} | mradermacher/Hexoteric-7B-GGUF | null | [
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"en"
] | TAGS
#transformers #gguf #mistral #mix #en #base_model-CalderaAI/Hexoteric-7B #license-apache-2.0 #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 | 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. -->
# GUE_EMP_H3K4me1-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_EMP_H3K4me1-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me1-seqsight_16384_512_22M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:26:26+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_EMP\_H3K4me1-seqsight\_16384\_512\_22M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5405
* F1 Score... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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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. -->
# GUE_EMP_H3K4me1-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_EMP_H3K4me1-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me1-seqsight_16384_512_22M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:27:15+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_EMP\_H3K4me1-seqsight\_16384\_512\_22M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5333
* F1 Score... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# GUE_EMP_H3K4me1-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_EMP_H3K4me1-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me1-seqsight_16384_512_22M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:27:30+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_EMP\_H3K4me1-seqsight\_16384\_512\_22M-L32\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5413
* F1 Sco... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# GUE_EMP_H3K36me3-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_EMP_H3K36me3-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K36me3-seqsight_16384_512_22M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_EMP\_H3K36me3-seqsight\_16384\_512\_22M-L1\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_EMP\_H3K36me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5035
* F1 Sc... | [
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... | [
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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_4iters_bs256_nodpo_only4w_iter_1
This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggingfa... | {"license": "mit", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "HuggingFaceH4/mistral-7b-sft-beta", "model-index": [{"name": "0.0_4iters_bs256_nodpo_only4w_iter_1", "results": []}]} | ShenaoZhang/0.0_4iters_bs256_nodpo_only4w_iter_1 | null | [
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"endpoints_compatible... | null | 2024-04-27T08:29:03+00:00 | [] | [] | TAGS
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|
# 0.0_4iters_bs256_nodpo_only4w_iter_1
This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
... | [
"# 0.0_4iters_bs256_nodpo_only4w_iter_1\n\nThis model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the updated and the original datasets.",
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"## Intended uses & limitations\n\nMore information needed",
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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. -->
# GUE_EMP_H3K36me3-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_EMP_H3K36me3-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K36me3-seqsight_16384_512_22M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:29:32+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_EMP\_H3K36me3-seqsight\_16384\_512\_22M-L8\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_EMP\_H3K36me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4898
* F1 Sc... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | null | # 🔎Taiwan-inquiry_7B_v2.1.gguf
- Model creator: [Joseph (Chen-Wei) Li](https://www.linkedin.com/in/joseph-li-3a453b231/)
- Original model: [Taiwan-inquiry_7B_2.1](https://huggingface.co/ChenWeiLi/Taiwan-inquiry_7B_v2.1)
| Name | Quant method | Bits | Size | Use case |
| ---- | :----: | :----: | :----: | ----- |
| [... | {"license": "apache-2.0"} | ChenWeiLi/Taiwan-inquiry_7B_v2.1.gguf | null | [
"gguf",
"license:apache-2.0",
"region:us"
] | null | 2024-04-27T08:32:40+00:00 | [] | [] | TAGS
#gguf #license-apache-2.0 #region-us
| Taiwan-inquiry\_7B\_v2.1.gguf
=============================
* Model creator: Joseph (Chen-Wei) Li
* Original model: Taiwan-inquiry\_7B\_2.1
Usage of the model
------------------
* The user can take on the role of a doctor, and the model can engage in conversation with you as if it were a patient.
* You can provi... | [] | [
"TAGS\n#gguf #license-apache-2.0 #region-us \n"
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17
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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": []} | swj0419/hp_all_STEP0000020 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
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- 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. -->
# GUE_EMP_H3K36me3-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_EMP_H3K36me3-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K36me3-seqsight_16384_512_22M-L32_f | null | [
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"region:us"
] | null | 2024-04-27T08:34:15+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_EMP\_H3K36me3-seqsight\_16384\_512\_22M-L32\_f
===================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_EMP\_H3K36me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4789
* F1 ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# radiopaedia_cl-llama3_8b-240426
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-l... | {"license": "other", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "meta-llama/Meta-Llama-3-8B", "model-index": [{"name": "radiopaedia_cl-llama3_8b-240426", "results": []}]} | Seoulsky/radiopaedia_cl-llama3_8b-240426 | null | [
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"generated_from_trainer",
"base_model:meta-llama/Meta-Llama-3-8B",
"license:other",
"region:us"
] | null | 2024-04-27T08:34:36+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-meta-llama/Meta-Llama-3-8B #license-other #region-us
|
# radiopaedia_cl-llama3_8b-240426
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Traini... | [
"# radiopaedia_cl-llama3_8b-240426\n\nThis model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the None dataset.",
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"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
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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": []} | HC-85/distilbert-lora-arxiv-multilabel | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | transformers | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/TitleOS/EinsteinBagel-8B
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up... | {"language": ["en"], "license": "llama3", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": "TitleOS/EinsteinBagel-8B", "quantized_by": "mradermacher"} | mradermacher/EinsteinBagel-8B-GGUF | null | [
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| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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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. -->
# CS505_COQE_viT5_total_Instruction0_SOPAL_v1
This model is a fine-tuned version of [VietAI/vit5-large](https://huggingface.co/Vie... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "VietAI/vit5-large", "model-index": [{"name": "CS505_COQE_viT5_total_Instruction0_SOPAL_v1", "results": []}]} | ThuyNT/CS505_COQE_viT5_total_Instruction0_SOPAL_v1 | null | [
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"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:VietAI/vit5-large",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-27T08:35:37+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-VietAI/vit5-large #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# CS505_COQE_viT5_total_Instruction0_SOPAL_v1
This model is a fine-tuned version of VietAI/vit5-large on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Tra... | [
"# CS505_COQE_viT5_total_Instruction0_SOPAL_v1\n\nThis model is a fine-tuned version of VietAI/vit5-large on the None dataset.",
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"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
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text-generation | transformers |
# OrpoLlama3-8B
This is an ORPO fine-tune of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on 1.5k steps of [mlabonne/orpo-dpo-mix-40k](https://huggingface.co/da... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["orpo"], "datasets": ["mlabonne/orpo-dpo-mix-40k"], "base_model": ["meta-llama/Meta-Llama-3-8B"]} | Muhammad2003/OrpoLlama3-8B | null | [
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|
# OrpoLlama3-8B
!image/jpeg
This is an ORPO fine-tune of meta-llama/Meta-Llama-3-8B on 1.5k steps of mlabonne/orpo-dpo-mix-40k.
## Usage
## Training curves
Wandb Report
!image/png
## Evaluation
!image/png
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image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Boya1_RMSProp_1-e5_10Epoch_swinv2-tiny-patch4-window16-256_fold3
This model is a fine-tuned version of [microsoft/swinv2-tiny-pa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/swinv2-tiny-patch4-window16-256", "model-index": [{"name": "Boya1_RMSProp_1-e5_10Epoch_swinv2-tiny-patch4-window16-256_fold3", "results": [{"task": {"type": "image-classification"... | onizukal/Boya1_RMSProp_1-e5_10Epoch_swinv2-tiny-patch4-window16-256_fold3 | null | [
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| Boya1\_RMSProp\_1-e5\_10Epoch\_swinv2-tiny-patch4-window16-256\_fold3
=====================================================================
This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window16-256 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0... | [
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text-generation | transformers |
# llama-lexi-star-uncensored-8b-slerp
llama-lexi-star-uncensored-8b-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Orenguteng/Llama-3-8B-LexiFun-Uncensored-V1](https://huggingface.co/Orenguteng/Llama-3-8B-LexiFun... | {"tags": ["merge", "mergekit", "lazymergekit", "Orenguteng/Llama-3-8B-LexiFun-Uncensored-V1", "liminerity/llama-3-8b-silent-star"], "base_model": ["Orenguteng/Llama-3-8B-LexiFun-Uncensored-V1", "liminerity/llama-3-8b-silent-star"]} | liminerity/llama-lexi-star-uncensored-8b-slerp | null | [
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# llama-lexi-star-uncensored-8b-slerp
llama-lexi-star-uncensored-8b-slerp is a merge of the following models using LazyMergekit:
* Orenguteng/Llama-3-8B-LexiFun-Uncensored-V1
* liminerity/llama-3-8b-silent-star
## Configuration
## Usage
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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": []} | Andro9669/flan-t5-ner | null | [
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text-generation | transformers |
# Model Card for Model ID
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## Model Details
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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
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# Joy10/bert-fine-tuned-cola
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unkno... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "bert-base-cased", "model-index": [{"name": "Joy10/bert-fine-tuned-cola", "results": []}]} | Joy10/bert-fine-tuned-cola | null | [
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| Joy10/bert-fine-tuned-cola
==========================
This model is a fine-tuned version of bert-base-cased on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.5055
* Validation Loss: 0.4208
* Epoch: 0
Model description
-----------------
More information needed
Inte... | [
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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. -->
# GUE_mouse_0-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_0-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_0-seqsight_16384_512_22M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_0-seqsight\_16384\_512\_22M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5635
* F1 Score: 0.7205
* A... | [
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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. -->
# GUE_mouse_0-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_0-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_0-seqsight_16384_512_22M-L8_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_0-seqsight\_16384\_512\_22M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5997
* F1 Score: 0.7167
* A... | [
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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. -->
# GUE_mouse_0-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_0-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_0-seqsight_16384_512_22M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:46:52+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_0-seqsight\_16384\_512\_22M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0468
* F1 Score: 0.6972
*... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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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. -->
# GUE_mouse_1-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_1-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_1-seqsight_16384_512_22M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:46:52+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_1-seqsight\_16384\_512\_22M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2586
* F1 Score: 0.8835
* A... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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image-text-to-text | xtuner |
# nullt3r/llava-llama-3-8b-v1_1-Q8_0-GGUF
This model was converted to GGUF format from [`xtuner/llava-llama-3-8b-v1_1`](https://huggingface.co/xtuner/llava-llama-3-8b-v1_1) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](ht... | {"library_name": "xtuner", "tags": ["llama-cpp", "gguf-my-repo"], "datasets": ["Lin-Chen/ShareGPT4V"], "pipeline_tag": "image-text-to-text"} | nullt3r/llava-llama-3-8b-v1_1-Q8_0-GGUF | null | [
"xtuner",
"gguf",
"llama-cpp",
"gguf-my-repo",
"image-text-to-text",
"dataset:Lin-Chen/ShareGPT4V",
"region:us"
] | null | 2024-04-27T08:47:03+00:00 | [] | [] | TAGS
#xtuner #gguf #llama-cpp #gguf-my-repo #image-text-to-text #dataset-Lin-Chen/ShareGPT4V #region-us
|
# nullt3r/llava-llama-3-8b-v1_1-Q8_0-GGUF
This model was converted to GGUF format from 'xtuner/llava-llama-3-8b-v1_1' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CLI:
Serve... | [
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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. -->
# GUE_mouse_1-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_1-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_1-seqsight_16384_512_22M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:47:33+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_1-seqsight\_16384\_512\_22M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2437
* F1 Score: 0.8923
* A... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# CS505_COQE_viT5_total_Instruction0_SOPAL_v1_h1
This model is a fine-tuned version of [VietAI/vit5-large](https://huggingface.co/... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "VietAI/vit5-large", "model-index": [{"name": "CS505_COQE_viT5_total_Instruction0_SOPAL_v1_h1", "results": []}]} | ThuyNT/CS505_COQE_viT5_total_Instruction0_SOPAL_v1_h1 | null | [
"transformers",
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"safetensors",
"t5",
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"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-27T08:47:44+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-VietAI/vit5-large #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# CS505_COQE_viT5_total_Instruction0_SOPAL_v1_h1
This model is a fine-tuned version of VietAI/vit5-large 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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"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"#... | [
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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. -->
# GUE_mouse_1-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_1-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_1-seqsight_16384_512_22M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:48:55+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_1-seqsight\_16384\_512\_22M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2345
* F1 Score: 0.8972
*... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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": []} | swj0419/hp_all_STEP0000040 | null | [
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#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
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- 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. -->
# GUE_mouse_4-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_4-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_4-seqsight_16384_512_22M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:50:29+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_4-seqsight\_16384\_512\_22M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6011
* F1 Score: 0.6739
* A... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# GUE_mouse_4-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_4-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_4-seqsight_16384_512_22M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:52:01+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_4-seqsight\_16384\_512\_22M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6171
* F1 Score: 0.6829
* A... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# distilhubert-finetuned-stutteringdetection
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["HareemFatima/stutteringdetection"], "metrics": ["accuracy"], "base_model": "ntu-spml/distilhubert", "model-index": [{"name": "distilhubert-finetuned-stutteringdetection", "results": [{"task": {"type": "audio-classification", "name": "Audio Clas... | HareemFatima/distilhubert-finetuned-stutterdetection | null | [
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| distilhubert-finetuned-stutteringdetection
==========================================
This model is a fine-tuned version of ntu-spml/distilhubert on the stuttering dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5717
* Accuracy: 0.9024
Model description
-----------------
More informa... | [
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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. -->
# GUE_mouse_4-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_4-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_4-seqsight_16384_512_22M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:53:29+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_4-seqsight\_16384\_512\_22M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6255
* F1 Score: 0.6676
*... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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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. -->
# GUE_mouse_3-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_3-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_3-seqsight_16384_512_22M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:53:30+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_3-seqsight\_16384\_512\_22M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6449
* F1 Score: 0.8032
* A... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# GUE_mouse_3-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_3-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_3-seqsight_16384_512_22M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:53:59+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_3-seqsight\_16384\_512\_22M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7940
* F1 Score: 0.8447
* A... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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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. -->
# GUE_mouse_3-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_3-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_3-seqsight_16384_512_22M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:54:45+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_3-seqsight\_16384\_512\_22M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8993
* F1 Score: 0.8409
*... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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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": []} | Andro9669/t5-ner | null | [
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"1910.09700"
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#transformers #safetensors #t5 #text2text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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": []} | siacus/Llama-3-8B-tweets-10 | 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 | 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. -->
# GUE_mouse_2-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_2-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_2-seqsight_16384_512_22M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:56:10+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_2-seqsight\_16384\_512\_22M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4210
* F1 Score: 0.8567
* A... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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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. -->
# GUE_mouse_2-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_2-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_2-seqsight_16384_512_22M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:56:23+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_2-seqsight\_16384\_512\_22M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4164
* F1 Score: 0.8719
* A... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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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": [{... | HusseinEid/Reinforce-Cartpole-v1 | null | [
"CartPole-v1",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2024-04-27T08:57:20+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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"TAGS\n#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n# 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 Lear... |
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. -->
# GUE_mouse_2-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_mouse_2-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_2-seqsight_16384_512_22M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:58:12+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_mouse\_2-seqsight\_16384\_512\_22M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_mouse\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3136
* F1 Score: 0.8628
*... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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": []} | swj0419/hp_all_STEP0000050 | null | [
"transformers",
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"llama",
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"arxiv:1910.09700",
"autotrain_compatible",
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"region:us"
] | null | 2024-04-27T08:58:23+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_splice_reconstructed-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_16384_512_22M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:59:33+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_splice\_reconstructed-seqsight\_16384\_512\_22M-L8\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed dataset.
It achieves the following results on the evaluation set:
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* ... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_splice_reconstructed-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_16384_512_22M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T08:59:38+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_splice\_reconstructed-seqsight\_16384\_512\_22M-L1\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed dataset.
It achieves the following results on the evaluation set:
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | null |
# gate369/llama-lexi-star-uncensored-8b-slerp-Q4_K_M-GGUF
This model was converted to GGUF format from [`liminerity/llama-lexi-star-uncensored-8b-slerp`](https://huggingface.co/liminerity/llama-lexi-star-uncensored-8b-slerp) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-m... | {"tags": ["merge", "mergekit", "lazymergekit", "Orenguteng/Llama-3-8B-LexiFun-Uncensored-V1", "liminerity/llama-3-8b-silent-star", "llama-cpp", "gguf-my-repo"], "base_model": ["Orenguteng/Llama-3-8B-LexiFun-Uncensored-V1", "liminerity/llama-3-8b-silent-star"]} | gate369/llama-lexi-star-uncensored-8b-slerp-Q4_K_M-GGUF | null | [
"gguf",
"merge",
"mergekit",
"lazymergekit",
"Orenguteng/Llama-3-8B-LexiFun-Uncensored-V1",
"liminerity/llama-3-8b-silent-star",
"llama-cpp",
"gguf-my-repo",
"base_model:Orenguteng/Llama-3-8B-LexiFun-Uncensored-V1",
"base_model:liminerity/llama-3-8b-silent-star",
"region:us"
] | null | 2024-04-27T09:00:01+00:00 | [] | [] | TAGS
#gguf #merge #mergekit #lazymergekit #Orenguteng/Llama-3-8B-LexiFun-Uncensored-V1 #liminerity/llama-3-8b-silent-star #llama-cpp #gguf-my-repo #base_model-Orenguteng/Llama-3-8B-LexiFun-Uncensored-V1 #base_model-liminerity/llama-3-8b-silent-star #region-us
|
# gate369/llama-lexi-star-uncensored-8b-slerp-Q4_K_M-GGUF
This model was converted to GGUF format from 'liminerity/llama-lexi-star-uncensored-8b-slerp' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL... | [
"# gate369/llama-lexi-star-uncensored-8b-slerp-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'liminerity/llama-lexi-star-uncensored-8b-slerp' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
"## Use with URL\n\nInstall URL through brew.\n\n... | [
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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. -->
# GUE_splice_reconstructed-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_51... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_16384_512_22M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:00:14+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_splice\_reconstructed-seqsight\_16384\_512\_22M-L32\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed dataset.
It achieves the following results on the evaluation set... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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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. -->
# GUE_tf_0-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_0-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_16384_512_22M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:01:00+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_0-seqsight\_16384\_512\_22M-L1\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3882
* F1 Score: 0.8304
* Accuracy: ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# GUE_tf_0-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_0-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_16384_512_22M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:02:01+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_0-seqsight\_16384\_512\_22M-L8\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3855
* F1 Score: 0.8285
* Accuracy: ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# GUE_tf_0-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_0-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_16384_512_22M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:02:11+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_0-seqsight\_16384\_512\_22M-L32\_f
===========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3866
* F1 Score: 0.8232
* Accuracy... | [
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reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framewor... | {"library_name": "stable-baselines3", "tags": ["SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SpaceInvadersNoFram... | Epoching/dqn-SpaceInvadersNoFrameskip-v4 | null | [
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"deep-reinforcement-learning",
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#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents... | [
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text-generation | transformers |
# miqu-evil-dpo
# **Model Details**
## Description
miqu-evil-dpo is fine-tuned model based on miqu, serving as a direct successor to PiVoT-0.1-Evil-a.
It is trained with evil-tune method applied.
<!-- prompt-template start -->
## Prompt template: Mistral Inst
```
<s> [INST] {inst} [... | {"language": ["en"], "license": "other", "tags": ["not-for-all-audiences"], "license_name": "miqu-license", "license_link": "LICENSE", "pipeline_tag": "text-generation"} | blockblockblock/miqu-evil-dpo-bpw5.5-exl2 | null | [
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#transformers #safetensors #llama #text-generation #not-for-all-audiences #conversational #en #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# miqu-evil-dpo
# Model Details
## Description
miqu-evil-dpo is fine-tuned model based on miqu, serving as a direct successor to PiVoT-0.1-Evil-a.
It is trained with evil-tune method applied.
!image/png
## Prompt template: Mistral Inst
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The AI model provided herein is intended for experimental... | [
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"## Prompt template: Mistral Inst",
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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. -->
# GUE_tf_1-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_1-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_16384_512_22M-L1_f | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_1-seqsight\_16384\_512\_22M-L1\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3563
* F1 Score: 0.8533
* Accuracy: ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | transformers |
# Uploaded model
- **Developed by:** xsa-dev
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/m... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | xsa-dev/hugs_llama3_technique_ft_16bit_lora | null | [
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|
# Uploaded model
- Developed by: xsa-dev
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
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text-generation | transformers |
# stablelm-2-zephyr-1.6b-slerpx9
stablelm-2-zephyr-1.6b-slerpx9 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [aipib/stablelm-2-zephyr-1.6b-slerpx3](https://huggingface.co/aipib/stablelm-2-zephyr-1.6b-slerpx3)
* [stabi... | {"tags": ["merge", "mergekit", "lazymergekit", "aipib/stablelm-2-zephyr-1.6b-slerpx3", "stabilityai/stablelm-2-zephyr-1_6b"], "base_model": ["aipib/stablelm-2-zephyr-1.6b-slerpx3", "stabilityai/stablelm-2-zephyr-1_6b"]} | aipib/stablelm-2-zephyr-1.6b-slerpx9 | null | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
"aipib/stablelm-2-zephyr-1.6b-slerpx3",
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"conversational",
"base_model:aipib/stablelm-2-zephyr-1.6b-slerpx3",
"base_model:stabilityai/stablelm-2-zephyr-1_6b",... | null | 2024-04-27T09:04:18+00:00 | [] | [] | TAGS
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# stablelm-2-zephyr-1.6b-slerpx9
stablelm-2-zephyr-1.6b-slerpx9 is a merge of the following models using LazyMergekit:
* aipib/stablelm-2-zephyr-1.6b-slerpx3
* stabilityai/stablelm-2-zephyr-1_6b
## Configuration
## Usage
| [
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# uzbek-sentiment-analysis
It achieves the following results on the evaluation set:
- eval_loss: 0.6374
- eval_accuracy: {'accurac... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "uzb-senAnalys", "results": []}]} | ai-nightcoder/uzbek-sentiment-analysis-v5 | null | [
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"text-classification",
"generated_from_trainer",
"base_model:distilbert-base-uncased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-27T09:04:25+00:00 | [] | [] | TAGS
#transformers #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# uzbek-sentiment-analysis
It achieves the following results on the evaluation set:
- eval_loss: 0.6374
- eval_accuracy: {'accuracy': 0.7862348178137651}
- eval_f1score: {'f1': 0.7880364308572618}
- eval_runtime: 7.593
- eval_samples_per_second: 162.65
- eval_steps_per_second: 20.414
- step: 0
## Model description... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | swj0419/hp_all_STEP0000060 | null | [
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"llama",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-27T09:06:52+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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. -->
# GUE_tf_1-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_1-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_16384_512_22M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:07:34+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_1-seqsight\_16384\_512\_22M-L8\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3459
* F1 Score: 0.8615
* Accuracy: ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# GUE_tf_1-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_1-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_16384_512_22M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:08:23+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_1-seqsight\_16384\_512\_22M-L32\_f
===========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3298
* F1 Score: 0.8619
* Accuracy... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# GUE_tf_4-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_4-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_4-seqsight_16384_512_22M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:08:23+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_4-seqsight\_16384\_512\_22M-L1\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3693
* F1 Score: 0.8407
* Accuracy: ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **PandaReachDense-v3**
This is a trained model of a **A2C** agent playing **PandaReachDense-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingf... | {"library_name": "stable-baselines3", "tags": ["PandaReachDense-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "PandaReachDense-v3", "type":... | hossniper/a2c-PandaReachDense-v3 | null | [
"stable-baselines3",
"PandaReachDense-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-27T09:09:24+00:00 | [] | [] | TAGS
#stable-baselines3 #PandaReachDense-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing PandaReachDense-v3
This is a trained model of a A2C agent playing PandaReachDense-v3
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# A2C Agent playing PandaReachDense-v3\nThis is a trained model of a A2C agent playing PandaReachDense-v3\nusing the stable-baselines3 library.",
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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. -->
# GUE_tf_4-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_4-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_4-seqsight_16384_512_22M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:10:23+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_4-seqsight\_16384\_512\_22M-L8\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3687
* F1 Score: 0.8417
* Accuracy: ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- 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: False
- bnb_4bit_quant_... | {"library_name": "peft"} | lekhapinninti/llama-2-7b-enhanced-10epoch | null | [
"peft",
"region:us"
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#peft #region-us
| ## Training procedure
The following 'bitsandbytes' quantization config was used during training:
- quant_method: bitsandbytes
- 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: False
- bnb_4bit_quant_... | [
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text-to-audio | 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. -->
# SpeechT5 Finetuned Vi - FredDYyy
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft... | {"language": ["vi"], "license": "mit", "tags": ["generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_13_0"], "base_model": "microsoft/speecht5_tts", "model-index": [{"name": "SpeechT5 Finetuned Vi - FredDYyy", "results": []}]} | FredDYyy/speecht5_finetuned_vi | null | [
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"base_model:microsoft/speecht5_tts",
"license:mit",
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| SpeechT5 Finetuned Vi - FredDYyy
================================
This model is a fine-tuned version of microsoft/speecht5\_tts on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4772
Model description
-----------------
More information needed
Intended uses & li... | [
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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": []} | Mohamedshaaban2001/llama3_text2sql | null | [
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"region:us"
] | null | 2024-04-27T09:12:27+00:00 | [
"1910.09700"
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#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-generation | transformers |
# Function Calling Fine-tuned Phi 3 Instruct
This model is fine-tuned for function calling.
- The model is suitable for commercial use.
Check out other fine-tuned function calling models [here](https://huggingface.co/collections/Trelis/function-calling-v3-657199ecbe378693925c7915).
## Quick Server Setup
Runpod one ... | {"language": ["en"], "tags": ["nlp", "code", "phi-3", "function-calling"], "datasets": ["Trelis/function_calling_v3"], "pipeline_tag": "text-generation", "widget": [{"messages": [{"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?"}]}], "extra_gated_prompt": "Purchase acce... | Trelis/Phi-3-mini-128k-instruct-function-calling | null | [
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"autotrain_compatible",
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] | null | 2024-04-27T09:12:46+00:00 | [] | [
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] | TAGS
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| Function Calling Fine-tuned Phi 3 Instruct
==========================================
This model is fine-tuned for function calling.
* The model is suitable for commercial use.
Check out other fine-tuned function calling models here.
Quick Server Setup
------------------
Runpod one click TGI template here. AW... | [
"### Using tokenizer.apply\\_chat\\_template\n\n\nFor an easier application of the prompt, you can set up as follows (note that the conversation below is complete, i.e. you need to remove assistant messages if you want to feed in the conversation to the model):\n\n\nSet up 'messages':\n\n\nwith 'FUNCTION\\_METADATA... | [
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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. -->
# GUE_tf_4-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_4-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_4-seqsight_16384_512_22M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:14:06+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_4-seqsight\_16384\_512\_22M-L32\_f
===========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3864
* F1 Score: 0.8470
* Accuracy... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# GUE_tf_3-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_3-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_3-seqsight_16384_512_22M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:14:17+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_3-seqsight\_16384\_512\_22M-L1\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5776
* F1 Score: 0.6912
* Accuracy: ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# GUE_tf_3-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_3-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_3-seqsight_16384_512_22M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:14:47+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_3-seqsight\_16384\_512\_22M-L8\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5640
* F1 Score: 0.7002
* Accuracy: ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# GUE_tf_3-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_3-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_3-seqsight_16384_512_22M-L32_f | null | [
"peft",
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"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_3-seqsight\_16384\_512\_22M-L32\_f
===========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5519
* F1 Score: 0.7047
* Accuracy... | [
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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": []} | shallow6414/9lg2om0 | 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. -->
# GUE_tf_2-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_2-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_2-seqsight_16384_512_22M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:15:38+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_2-seqsight\_16384\_512\_22M-L1\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4637
* F1 Score: 0.7756
* Accuracy: ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Boya1_RMSProp_1-e5_10Epoch_swinv2-tiny-patch4-window16-256_fold4
This model is a fine-tuned version of [microsoft/swinv2-tiny-pa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/swinv2-tiny-patch4-window16-256", "model-index": [{"name": "Boya1_RMSProp_1-e5_10Epoch_swinv2-tiny-patch4-window16-256_fold4", "results": [{"task": {"type": "image-classification"... | onizukal/Boya1_RMSProp_1-e5_10Epoch_swinv2-tiny-patch4-window16-256_fold4 | null | [
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| Boya1\_RMSProp\_1-e5\_10Epoch\_swinv2-tiny-patch4-window16-256\_fold4
=====================================================================
This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window16-256 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0... | [
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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. -->
# GUE_tf_2-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_2-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_2-seqsight_16384_512_22M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:16:17+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_2-seqsight\_16384\_512\_22M-L32\_f
===========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4840
* F1 Score: 0.7789
* Accuracy... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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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. -->
# GUE_tf_2-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_tf_2-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_2-seqsight_16384_512_22M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:16:17+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_tf\_2-seqsight\_16384\_512\_22M-L8\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_tf\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4616
* F1 Score: 0.7690
* Accuracy: ... | [
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text-generation | transformers |
# stablelm-2-zephyr-1.6b-slerpx10
stablelm-2-zephyr-1.6b-slerpx10 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [aipib/stablelm-2-zephyr-1.6b-slerpx9](https://huggingface.co/aipib/stablelm-2-zephyr-1.6b-slerpx9)
* [sta... | {"tags": ["merge", "mergekit", "lazymergekit", "aipib/stablelm-2-zephyr-1.6b-slerpx9", "stabilityai/stablelm-2-zephyr-1_6b"], "base_model": ["aipib/stablelm-2-zephyr-1.6b-slerpx9", "stabilityai/stablelm-2-zephyr-1_6b"]} | aipib/stablelm-2-zephyr-1.6b-slerpx10 | null | [
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"base_model:stabilityai/stablelm-2-zephyr-1_6b",... | null | 2024-04-27T09:16:35+00:00 | [] | [] | TAGS
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# stablelm-2-zephyr-1.6b-slerpx10
stablelm-2-zephyr-1.6b-slerpx10 is a merge of the following models using LazyMergekit:
* aipib/stablelm-2-zephyr-1.6b-slerpx9
* stabilityai/stablelm-2-zephyr-1_6b
## Configuration
## Usage
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | Andro9669/gemma-7b-ner | null | [
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# Model Card for Model ID
## Model Details
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** ... | {"library_name": "peft", "base_model": "mistralai/Mistral-7B-Instruct-v0.2"} | nizamudma/Enlighten_Instruct_Mistral | null | [
"peft",
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"1910.09700"
] | [] | TAGS
#peft #safetensors #arxiv-1910.09700 #base_model-mistralai/Mistral-7B-Instruct-v0.2 #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
#... | [
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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. -->
# 0.001_4iters_bs128_nodpo_only4w_iter_3
This model is a fine-tuned version of [ShenaoZhang/0.001_4iters_bs128_nodpo_only4w_iter_2... | {"license": "mit", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "ShenaoZhang/0.001_4iters_bs128_nodpo_only4w_iter_2", "model-index": [{"name": "0.001_4iters_bs128_nodpo_only4w_iter_3", "results": []}]} | ShenaoZhang/0.001_4iters_bs128_nodpo_only4w_iter_3 | null | [
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"end... | null | 2024-04-27T09:19:52+00:00 | [] | [] | TAGS
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# 0.001_4iters_bs128_nodpo_only4w_iter_3
This model is a fine-tuned version of ShenaoZhang/0.001_4iters_bs128_nodpo_only4w_iter_2 on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More i... | [
"# 0.001_4iters_bs128_nodpo_only4w_iter_3\n\nThis model is a fine-tuned version of ShenaoZhang/0.001_4iters_bs128_nodpo_only4w_iter_2 on the updated and the original datasets.",
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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. -->
# GUE_virus_covid-seqsight_16384_512_22M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_virus_covid-seqsight_16384_512_22M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_virus_covid-seqsight_16384_512_22M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_virus\_covid-seqsight\_16384\_512\_22M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_virus\_covid dataset.
It achieves the following results on the evaluation set:
* Loss: 1.6944
* F1 Score... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# GUE_virus_covid-seqsight_16384_512_22M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_virus_covid-seqsight_16384_512_22M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_virus_covid-seqsight_16384_512_22M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:20:26+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_virus\_covid-seqsight\_16384\_512\_22M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_virus\_covid dataset.
It achieves the following results on the evaluation set:
* Loss: 1.3754
* F1 Score... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# GUE_virus_covid-seqsight_16384_512_22M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_22M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_22M", "model-index": [{"name": "GUE_virus_covid-seqsight_16384_512_22M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_virus_covid-seqsight_16384_512_22M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_22M",
"region:us"
] | null | 2024-04-27T09:21:01+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_22M #region-us
| GUE\_virus\_covid-seqsight\_16384\_512\_22M-L32\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_22M on the mahdibaghbanzadeh/GUE\_virus\_covid dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1612
* F1 Sco... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# CS505_COQE_viT5_total_Instruction0_SAOPL_v1
This model is a fine-tuned version of [VietAI/vit5-large](https://huggingface.co/Vie... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "VietAI/vit5-large", "model-index": [{"name": "CS505_COQE_viT5_total_Instruction0_SAOPL_v1", "results": []}]} | ThuyNT/CS505_COQE_viT5_total_Instruction0_SAOPL_v1 | null | [
"transformers",
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"base_model:VietAI/vit5-large",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-27T09:21:29+00:00 | [] | [] | TAGS
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|
# CS505_COQE_viT5_total_Instruction0_SAOPL_v1
This model is a fine-tuned version of VietAI/vit5-large on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Tra... | [
"# CS505_COQE_viT5_total_Instruction0_SAOPL_v1\n\nThis model is a fine-tuned version of VietAI/vit5-large on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## T... | [
"TAGS\n#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-VietAI/vit5-large #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
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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. -->
# nepali_t5
This model is a fine-tuned version of [rujengelal/nepali_t5](https://huggingface.co/rujengelal/nepali_t5) on an unknow... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "base_model": "rujengelal/nepali_t5", "model-index": [{"name": "nepali_t5", "results": []}]} | rujengelal/nepali_t5 | null | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:rujengelal/nepali_t5",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-27T09:26:01+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-rujengelal/nepali_t5 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| nepali\_t5
==========
This model is a fine-tuned version of rujengelal/nepali\_t5 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.6633
* Bleu: 6.3134
* Gen Len: 15.9835
Model description
-----------------
More information needed
Intended uses & limitations
-----------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 10\n* mixed\\_preci... | [
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