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null | transformers |
# Uploaded model
- **Developed by:** tingting
- **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/... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | tingting/llama3_lora_model_Data_80 | null | [
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"en",
"base_model:unsloth/llama-3-8b-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
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|
# Uploaded model
- Developed by: tingting
- 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-to-image | diffusers |
# kisaragi_mix API Inference
## Get API Key
Get API key from [ModelsLab API](http://modelslab.com), No Payment needed.
Replace Key in below code, change **model_id** to "kisaragimix"
Coding in... | {"license": "creativeml-openrail-m", "tags": ["modelslab.com", "stable-diffusion-api", "text-to-image", "ultra-realistic"], "pinned": true} | stablediffusionapi/kisaragimix | null | [
"diffusers",
"modelslab.com",
"stable-diffusion-api",
"text-to-image",
"ultra-realistic",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | null | 2024-04-29T22:09:47+00:00 | [] | [] | TAGS
#diffusers #modelslab.com #stable-diffusion-api #text-to-image #ultra-realistic #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
|
# kisaragi_mix API Inference
!generated from URL
## Get API Key
Get API key from ModelsLab API, No Payment needed.
Replace Key in below code, change model_id to "kisaragimix"
Coding in PHP/Node/Java etc? Have a look at docs for more code examples: View docs
Try model for free: Generate Images
Model link: View ... | [
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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": []} | axel-rda/ARIA-70B-V3-qlora-sft-adapters | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-29T22:10:52+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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": []} | abc88767/model11 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | null |
# MeliodasNeuralsynthesis-7B
MeliodasNeuralsynthesis-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
## 🧩 Configuration
```yaml
models:
- model: mistralai/Mistral-7B-v0.1
- model: AurelPx/Meliodas-7b-dare
- model: Kukedlc/NeuralSynthesi... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"]} | automerger/MeliodasNeuralsynthesis-7B | null | [
"merge",
"mergekit",
"lazymergekit",
"automerger",
"license:apache-2.0",
"region:us"
] | null | 2024-04-29T22:11:03+00:00 | [] | [] | TAGS
#merge #mergekit #lazymergekit #automerger #license-apache-2.0 #region-us
|
# MeliodasNeuralsynthesis-7B
MeliodasNeuralsynthesis-7B is an automated merge created by Maxime Labonne using the following configuration.
## Configuration
## Usage
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text-generation | null | # Llama-3-8b-64k-PoSE-GGUF
- Original model: [Llama-3-8b-64k-PoSE](https://huggingface.co/winglian/Llama-3-8b-64k-PoSE)
<!-- description start -->
## Description
This repo contains GGUF format model files for [Llama-3-8b-64k-PoSE](https://huggingface.co/winglian/Llama-3-8b-64k-PoSE).
<!-- description end -->
<!-- RE... | {"language": ["en"], "tags": ["facebook", "meta", "pytorch", "llama", "llama-3", "axolotl", "GGUF"], "pipeline_tag": "text-generation", "quantized_by": "andrijdavid"} | LiteLLMs/Llama-3-8b-64k-PoSE-GGUF | null | [
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"meta",
"pytorch",
"llama",
"llama-3",
"axolotl",
"GGUF",
"text-generation",
"en",
"arxiv:2309.10400",
"region:us"
] | null | 2024-04-29T22:11:12+00:00 | [
"2309.10400"
] | [
"en"
] | TAGS
#gguf #facebook #meta #pytorch #llama #llama-3 #axolotl #GGUF #text-generation #en #arxiv-2309.10400 #region-us
| Llama-3-8b-64k-PoSE-GGUF
========================
* Original model: Llama-3-8b-64k-PoSE
Description
-----------
This repo contains GGUF format model files for Llama-3-8b-64k-PoSE.
### About GGUF
GGUF is a new format introduced by the URL team on August 21st 2023. It is a replacement for GGML, which is no long... | [
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null | transformers |
# Uploaded model
- **Developed by:** tingting
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-bnb-4bit
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unslot... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-bnb-4bit"} | tingting/mistral_lora_model_Data_50 | null | [
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"base_model:unsloth/mistral-7b-bnb-4bit",
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|
# Uploaded model
- Developed by: tingting
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H4-seqsight_16384_512_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H4-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4-seqsight_16384_512_34M-L32_f | null | [
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H4-seqsight\_16384\_512\_34M-L32\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2865
* F1 Score: 0.8966
* Ac... | [
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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_H3-seqsight_16384_512_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https://... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H3-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3-seqsight_16384_512_34M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3-seqsight\_16384\_512\_34M-L1\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3 dataset.
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* Loss: 0.3038
* F1 Score: 0.8818
* Accu... | [
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text-generation | transformers |
## Llamacpp imatrix Quantizations of starcoder2-15b-instruct-v0.1
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2756">b2756</a> for quantization.
Original model: https://huggingface.co/bigcode/starcoder2-15b-instruct-v0.1
... | {"license": "bigcode-openrail-m", "library_name": "transformers", "tags": ["code"], "datasets": ["bigcode/self-oss-instruct-sc2-exec-filter-50k"], "pipeline_tag": "text-generation", "base_model": "bigcode/starcoder2-15b", "quantized_by": "bartowski", "model-index": [{"name": "starcoder2-15b-instruct-v0.1", "results": [... | bartowski/starcoder2-15b-instruct-v0.1-GGUF | null | [
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| Llamacpp imatrix Quantizations of starcoder2-15b-instruct-v0.1
--------------------------------------------------------------
Using <a href="URL release <a href="URL for quantization.
Original model: URL
All quants made using imatrix option with dataset provided by Kalomaze here
Prompt format
-------------
No... | [] | [
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] |
text-generation | transformers |
# Uploaded model
- **Developed by:** axel-rda
- **License:** apache-2.0
- **Finetuned from model :** Faradaylab/ARIA-70B-V3
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/main/... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "Faradaylab/ARIA-70B-V3"} | axel-rda/ARIA-70B-V3-qlora-sft | null | [
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|
# Uploaded model
- Developed by: axel-rda
- License: apache-2.0
- Finetuned from model : Faradaylab/ARIA-70B-V3
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3-seqsight_16384_512_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https://... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H3-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3-seqsight_16384_512_34M-L8_f | null | [
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"safetensors",
"generated_from_trainer",
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3-seqsight\_16384\_512\_34M-L8\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3629
* F1 Score: 0.8684
* Accu... | [
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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": []} | lunarsylph/mooncell_v33 | null | [
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"region:us"
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"1910.09700"
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#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-to-image | diffusers |
# nagatsuki_mix API Inference
## Get API Key
Get API key from [ModelsLab API](http://modelslab.com), No Payment needed.
Replace Key in below code, change **model_id** to "nagatsukimix"
Coding... | {"license": "creativeml-openrail-m", "tags": ["modelslab.com", "stable-diffusion-api", "text-to-image", "ultra-realistic"], "pinned": true} | stablediffusionapi/nagatsukimix | null | [
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|
# nagatsuki_mix API Inference
!generated from URL
## Get API Key
Get API key from ModelsLab API, No Payment needed.
Replace Key in below code, change model_id to "nagatsukimix"
Coding in PHP/Node/Java etc? Have a look at docs for more code examples: View docs
Try model for free: Generate Images
Model link: Vie... | [
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text-generation | keras-nlp | This is a [`GPT2` model](https://keras.io/api/keras_nlp/models/gpt2) uploaded using the KerasNLP library and can be used with JAX, TensorFlow, and PyTorch backends.
This model is related to a `CausalLM` task.
Model config:
* **name:** gpt2_backbone
* **trainable:** True
* **vocabulary_size:** 50257
* **num_layers:** 1... | {"library_name": "keras-nlp", "pipeline_tag": "text-generation"} | samanehs/finetuned_gpt2 | null | [
"keras-nlp",
"text-generation",
"region:us"
] | null | 2024-04-29T22:24:27+00:00 | [] | [] | TAGS
#keras-nlp #text-generation #region-us
| This is a 'GPT2' model uploaded using the KerasNLP library and can be used with JAX, TensorFlow, and PyTorch backends.
This model is related to a 'CausalLM' task.
Model config:
* name: gpt2_backbone
* trainable: True
* vocabulary_size: 50257
* num_layers: 12
* num_heads: 12
* hidden_dim: 768
* intermediate_dim: 3072
*... | [] | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | cilantro9246/31anfwt | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
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"region:us"
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"1910.09700"
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#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | transformers |
# Uploaded model
- **Developed by:** tingting
- **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/... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | tingting/llama3_lora_model_Data_3200 | null | [
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|
# Uploaded model
- Developed by: tingting
- 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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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# whisper-bs-cs-train-aug-test-aug2
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whis... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice_11_0"], "metrics": ["wer"], "base_model": "openai/whisper-base", "model-index": [{"name": "whisper-bs-cs-train-aug-test-aug2", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "... | LadislavVasina1/whisper-bs-cs-train-aug-test-aug2 | null | [
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| whisper-bs-cs-train-aug-test-aug2
=================================
This model is a fine-tuned version of openai/whisper-base on the common\_voice\_11\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6875
* Wer: 54.1533
Model description
-----------------
More information needed
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1... | [
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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_H4ac-seqsight_16384_512_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H4ac-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4ac-seqsight_16384_512_34M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H4ac-seqsight\_16384\_512\_34M-L1\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H4ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5598
* F1 Score: 0.7325
... | [
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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_H3-seqsight_16384_512_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H3-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3-seqsight_16384_512_34M-L32_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3-seqsight\_16384\_512\_34M-L32\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3581
* F1 Score: 0.8804
* Ac... | [
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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": []} | shallow6414/6my36hg | null | [
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#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
- Model type:
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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_H4ac-seqsight_16384_512_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H4ac-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4ac-seqsight_16384_512_34M-L8_f | null | [
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"safetensors",
"generated_from_trainer",
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H4ac-seqsight\_16384\_512\_34M-L8\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H4ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5616
* F1 Score: 0.7387
... | [
"### 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_H4ac-seqsight_16384_512_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H4ac-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4ac-seqsight_16384_512_34M-L32_f | null | [
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"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H4ac-seqsight\_16384\_512\_34M-L32\_f
===============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H4ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5538
* F1 Score: 0.738... | [
"### 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_H3K79me3-seqsight_16384_512_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H3K79me3-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K79me3-seqsight_16384_512_34M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3K79me3-seqsight\_16384\_512\_34M-L1\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K79me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4351
* F1 Sc... | [
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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_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H3K79me3-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K79me3-seqsight_16384_512_34M-L8_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3K79me3-seqsight\_16384\_512\_34M-L8\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K79me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4277
* 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 | 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_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H3K79me3-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K79me3-seqsight_16384_512_34M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T22:35:33+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3K79me3-seqsight\_16384\_512\_34M-L32\_f
===================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K79me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4507
* F1 ... | [
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question-answering | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distil_final
This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an u... | {"language": ["ar"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-cased", "model-index": [{"name": "distil_final", "results": []}]} | gp-tar4/QA_FineTuned_DistilBert-based-uncased | null | [
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#transformers #safetensors #distilbert #question-answering #generated_from_trainer #ar #base_model-distilbert-base-cased #license-apache-2.0 #endpoints_compatible #region-us
| distil\_final
=============
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 3.5805
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More info... | [
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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": []} | BotoxBernd/SQL-Generation-mistral-7B-v0.2 | null | [
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"safetensors",
"mistral",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-29T22:41:02+00:00 | [
"1910.09700"
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#transformers #safetensors #mistral #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="whiskeyriot/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional... | {"tags": ["FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-noSlippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4-no_slippery", "type": ... | whiskeyriot/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-29T22:42:23+00:00 | [] | [] | TAGS
#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
## Usage
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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. -->
# sentiment-analysis-model-trained
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbe... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "sentiment-analysis-model-trained", "results": []}]} | Lasghar/sentiment-analysis-model-trained | null | [
"transformers",
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"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert-base-uncased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-29T22:43:23+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
| sentiment-analysis-model-trained
================================
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3513
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: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="whiskeyriot/Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.32 +/- ... | whiskeyriot/Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-29T22:46:18+00:00 | [] | [] | TAGS
#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
## Usage
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] |
feature-extraction | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | stvhuang/rcr-run-5pqr6lwp-90396-master-0_20240402T105012-ep40 | null | [
"transformers",
"safetensors",
"xlm-roberta",
"feature-extraction",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-29T22:46:39+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #xlm-roberta #feature-extraction #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me1-seqsight_16384_512_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H3K4me1-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me1-seqsight_16384_512_34M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T22:48:07+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3K4me1-seqsight\_16384\_512\_34M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5145
* 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_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H3K4me1-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me1-seqsight_16384_512_34M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T22:48:31+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3K4me1-seqsight\_16384\_512\_34M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5125
* 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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text-to-image | diffusers | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### vesttieandtux2 Dreambooth model trained by enriq3 with TheLastBen's fast-DreamBooth notebook
| {} | enriq3/vesttieandtux2 | null | [
"diffusers",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | null | 2024-04-29T22:48:50+00:00 | [] | [] | TAGS
#diffusers #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
| ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### vesttieandtux2 Dreambooth model trained by enriq3 with TheLastBen's fast-DreamBooth notebook
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] |
text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GPT2_DocBot_SonatafyAI_V3
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It ac... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "gpt2", "model-index": [{"name": "GPT2_DocBot_SonatafyAI_V3", "results": []}]} | ajtamayoh/GPT2_DocBot_SonatafyAI_V3 | null | [
"transformers",
"tensorboard",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"base_model:gpt2",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-29T22:51:22+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #gpt2 #text-generation #generated_from_trainer #base_model-gpt2 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| GPT2\_DocBot\_SonatafyAI\_V3
============================
This model is a fine-tuned version of gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.8062
Model description
-----------------
More information needed
Intended uses & limitations
--------------------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 4\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: 5",
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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_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H3K4me1-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me1-seqsight_16384_512_34M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T22:51:42+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3K4me1-seqsight\_16384\_512\_34M-L32\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5161
* 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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question-answering | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-squad
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/d... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "distilbert-base-uncased-finetuned-squad", "results": []}]} | ahmad01010101/distilbert-base-uncased-finetuned-squad | null | [
"transformers",
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"safetensors",
"distilbert",
"question-answering",
"generated_from_trainer",
"base_model:distilbert-base-uncased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-29T22:53:10+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #distilbert #question-answering #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-squad
=======================================
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1599
Model description
-----------------
More information needed
Intended uses... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
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text-generation | transformers |
An updated version of the previous model. In this one, I have not yet found any problems with word duplication.
02.05.24 Model updates, new versions are in the v1.1 branch.
Link to original model and script:
- openlynn/Llama-3-Soliloquy-8B-v1.5-64k: https://huggingface.co/openlynn/Llama-3-Soliloquy-8B-v1.5-64k
- Fan... | {"language": ["en"], "license": "cc-by-nc-sa-4.0", "library_name": "transformers", "tags": ["llama", "text-generation-inference"], "pipeline_tag": "text-generation"} | SolidSnacke/Llama-3-Soliloquy-8B-v1.5-64k-i-GGUF | null | [
"transformers",
"gguf",
"llama",
"text-generation-inference",
"text-generation",
"en",
"license:cc-by-nc-sa-4.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-29T22:53:28+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #llama #text-generation-inference #text-generation #en #license-cc-by-nc-sa-4.0 #endpoints_compatible #region-us
|
An updated version of the previous model. In this one, I have not yet found any problems with word duplication.
02.05.24 Model updates, new versions are in the v1.1 branch.
Link to original model and script:
- openlynn/Llama-3-Soliloquy-8B-v1.5-64k: URL
- FantasiaFoundry/GGUF-Quantization-Script: URL | [] | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0428HMA2
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset.... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0428HMA2", "results": []}]} | Litzy619/O0428HMA2 | null | [
"safetensors",
"generated_from_trainer",
"base_model:allenai/OLMo-1B",
"license:apache-2.0",
"region:us"
] | null | 2024-04-29T22:53:54+00:00 | [] | [] | TAGS
#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0428HMA2
=========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0559
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 16\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0428HMA3
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset.... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0428HMA3", "results": []}]} | Litzy619/O0428HMA3 | null | [
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#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0428HMA3
=========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0534
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
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. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | cilantro9246/tlvmpdp | null | [
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text2text-generation | peft | ## llama-2-13b-code-alpaca
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
Trained for 3 epochs on `theblackcat102/evol-codealpaca-v1` dataset, scored... | {"language": ["en"], "license": "cc-by-nc-4.0", "library_name": "peft", "datasets": ["theblackcat102/evol-codealpaca-v1"], "pipeline_tag": "text2text-generation"} | DTang161/ModelMergingCode | null | [
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| ## llama-2-13b-code-alpaca
<img src="URL alt="Built with Axolotl" width="200" height="32"/>
Trained for 3 epochs on 'theblackcat102/evol-codealpaca-v1' dataset, scored decent on locally run perplexity at 4.36.
## Axolotl config used
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## Training procedure
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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": []} | Quac/Indian-Edu-SFT-llama-3-8B | null | [
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text-generation | transformers | # Llama-3-8B-Ultra-Instruct
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
Hello everyone this is Dampf, creator of the Destroyer series!
*looks around* Oh, now I'm on Elinas' HF account. As you can see, I'm quite the traveler!
This time, I'm introducing... | {"license": "llama3", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["Undi95/Meta-Llama-3-8B-Instruct-hf"]} | elinas/Llama-3-8B-Ultra-Instruct | null | [
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| Llama-3-8B-Ultra-Instruct
=========================
This is a merge of pre-trained language models created using mergekit.
Hello everyone this is Dampf, creator of the Destroyer series!
*looks around* Oh, now I'm on Elinas' HF account. As you can see, I'm quite the traveler!
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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. -->
# mbart-large-50-bcoqa
This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "facebook/mbart-large-50", "model-index": [{"name": "mbart-large-50-bcoqa", "results": []}]} | arbitropy/mbart-large-50-bcoqa | null | [
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| mbart-large-50-bcoqa
====================
This model is a fine-tuned version of facebook/mbart-large-50 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0137
Model description
-----------------
More information needed
Intended uses & limitations
-------------------------... | [
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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": [{... | haytamelouarrat/Reinforce-CartPole-v1 | null | [
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#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
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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. -->
# norllm-ai-normistral-7b-align-scan
This model is a fine-tuned version of [data/norllm-ai-normistral-7b-sft-qlora](https://huggin... | {"library_name": "peft", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer"], "datasets": ["hugodk-sch/aftonposten_title_prefs"], "base_model": "NorLLM-AI/NorMistral-7B", "model-index": [{"name": "norllm-ai-normistral-7b-align-scan", "results": []}]} | hugodk-sch/norllm-ai-normistral-7b-align-scan | null | [
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"base_model:NorLLM-AI/NorMistral-7B",
"4-bit",
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| norllm-ai-normistral-7b-align-scan
==================================
This model is a fine-tuned version of data/norllm-ai-normistral-7b-sft-qlora on the hugodk-sch/aftonposten\_title\_prefs dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9294
* Rewards/chosen: -0.0900
* Rewards/rejected... | [
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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/i604il5 | null | [
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text-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | profoz/parent_malicious_model | null | [
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"arxiv: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.
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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": []} | tsharish/Mistral-7B-Inst-v0.2-pubmed-1k_adapter | null | [
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#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
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- Shared 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_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H3K36me3-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K36me3-seqsight_16384_512_34M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:05:51+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3K36me3-seqsight\_16384\_512\_34M-L1\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K36me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4546
* 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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"### 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_EMP_H3K36me3-seqsight_16384_512_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H3K36me3-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K36me3-seqsight_16384_512_34M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:06:44+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3K36me3-seqsight\_16384\_512\_34M-L8\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K36me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4506
* 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 | 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. -->
# EstigiaxLlama
This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLl... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0", "model-index": [{"name": "EstigiaxLlama", "results": []}]} | franciscobdl/EstigiaxLlama | null | [
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"tensorboard",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"license:apache-2.0",
"region:us"
] | null | 2024-04-29T23:06:57+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #base_model-TinyLlama/TinyLlama-1.1B-Chat-v1.0 #license-apache-2.0 #region-us
|
# EstigiaxLlama
This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-Chat-v1.0 on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperpa... | [
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"# EstigiaxLlama\n\nThis model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-Chat-v1.0 on the None dataset.",
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null | null |
# DDPO trained model
num_epochs=20
train_gradient_accumulation_steps=1
sample_num_steps=30
sample_batch_size=8
train_batch_size=8
sample_num_batches_per_epoch=32
based off of stabilityai/stable-diffusion-2-base
and then trained off of None
| {} | jlbaker361/ddpo-runway-image_reward-hard | null | [
"region:us"
] | null | 2024-04-29T23:07:08+00:00 | [] | [] | TAGS
#region-us
|
# DDPO trained model
num_epochs=20
train_gradient_accumulation_steps=1
sample_num_steps=30
sample_batch_size=8
train_batch_size=8
sample_num_batches_per_epoch=32
based off of stabilityai/stable-diffusion-2-base
and then trained off of None
| [
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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_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_0-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_0-seqsight_16384_512_34M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:07:22+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_0-seqsight\_16384\_512\_34M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5838
* F1 Score: 0.7160
* 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_EMP_H3K36me3-seqsight_16384_512_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H3K36me3-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K36me3-seqsight_16384_512_34M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:07:32+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3K36me3-seqsight\_16384\_512\_34M-L32\_f
===================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K36me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4544
* 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. -->
# GUE_mouse_0-seqsight_16384_512_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_0-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_0-seqsight_16384_512_34M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:07:34+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_0-seqsight\_16384\_512\_34M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9978
* F1 Score: 0.7109
* 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_0-seqsight_16384_512_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_0-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_0-seqsight_16384_512_34M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:08:18+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_0-seqsight\_16384\_512\_34M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1630
* F1 Score: 0.7037
*... | [
"### 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_mouse_1-seqsight_16384_512_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_1-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_1-seqsight_16384_512_34M-L1_f | null | [
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"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_1-seqsight\_16384\_512\_34M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2519
* F1 Score: 0.8867
* A... | [
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text-generation | null |
## Exllama v2 Quantizations of NPC-LLM-3_8B
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.20">turboderp's ExLlamaV2 v0.0.20</a> for quantization.
<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
Each branch contains a... | {"language": ["en"], "license": "mit", "quantized_by": "bartowski", "pipeline_tag": "text-generation"} | bartowski/NPC-LLM-3_8B-exl2 | null | [
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|
## Exllama v2 Quantizations of NPC-LLM-3_8B
Using <a href="URL ExLlamaV2 v0.0.20</a> for quantization.
<b>The "main" branch only contains the URL, download one of the other branches for the model (see below)</b>
Each branch contains an individual bits per weight, with the main one containing only the URL for furthe... | [
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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": []} | franciscobdl/EstigiaxTinyLlama | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 0.01_4iters_bs256_nodpo_full6w_userresponse_iter_2
This model is a fine-tuned version of [ShenaoZhang/0.01_4iters_bs256_nodpo_fu... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "ShenaoZhang/0.01_4iters_bs256_nodpo_full6w_userresponse_iter_1", "model-index": [{"name": "0.01_4iters_bs256_nodpo_full6w_userresponse_iter_2", "result... | ShenaoZhang/0.01_4iters_bs256_nodpo_full6w_userresponse_iter_2 | null | [
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# 0.01_4iters_bs256_nodpo_full6w_userresponse_iter_2
This model is a fine-tuned version of ShenaoZhang/0.01_4iters_bs256_nodpo_full6w_userresponse_iter_1 on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and... | [
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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": []} | Shaleen123/llama3-code-4bit | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | 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_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_1-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_1-seqsight_16384_512_34M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:17:46+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_1-seqsight\_16384\_512\_34M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2345
* F1 Score: 0.8950
* 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_1-seqsight_16384_512_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_1-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_1-seqsight_16384_512_34M-L32_f | null | [
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] | null | 2024-04-29T23:17:52+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_1-seqsight\_16384\_512\_34M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2318
* F1 Score: 0.9017
*... | [
"### 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_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_4-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_4-seqsight_16384_512_34M-L1_f | null | [
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"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:18:40+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_4-seqsight\_16384\_512\_34M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5700
* F1 Score: 0.6988
* 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_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_4-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_4-seqsight_16384_512_34M-L8_f | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:20:03+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_4-seqsight\_16384\_512\_34M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5910
* F1 Score: 0.7116
* A... | [
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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... | {"license": "apache-2.0", "library_name": "transformers"} | Shaleen123/llama3-code-8bit | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | 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-v0.1"} | Akshay24/mistral7b_finetuned_tijori | null | [
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text-generation | gguf | # Megac4ai-command-r-plus-gguf
These are quantized GGUF versions of [nitky/Megac4ai-command-r-plus](https://huggingface.co/nitky/Megac4ai-command-r-plus). Please check the original model for license and more details.
## Results for non-English languages (Japanese)
| Model | Output Quality | Notes |
|-------|--------... | {"language": ["en", "fr", "de", "es", "it", "pt", "ja", "ko", "zh", "ar"], "license": "cc-by-nc-4.0", "library_name": "gguf", "tags": ["mergekit", "merge"], "base_model": ["CohereForAI/c4ai-command-r-plus"], "pipeline_tag": "text-generation"} | nitky/Megac4ai-command-r-plus-gguf | null | [
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| Megac4ai-command-r-plus-gguf
============================
These are quantized GGUF versions of nitky/Megac4ai-command-r-plus. Please check the original model for license and more details.
Results for non-English languages (Japanese)
--------------------------------------------
Model: Megac4ai-command-r-plus-IQ3\_... | [] | [
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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_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_4-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_4-seqsight_16384_512_34M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_4-seqsight\_16384\_512\_34M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6491
* F1 Score: 0.7024
*... | [
"### 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": []} | cilantro9246/q95707u | 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_mouse_3-seqsight_16384_512_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_3-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_3-seqsight_16384_512_34M-L1_f | null | [
"peft",
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"generated_from_trainer",
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_3-seqsight\_16384\_512\_34M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4306
* F1 Score: 0.8158
* 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 | null | # Smaug-72B-v0.1-GGUF
- Original model: [Smaug-72B-v0.1](https://huggingface.co/abacusai/Smaug-72B-v0.1)
<!-- description start -->
## Description
This repo contains GGUF format model files for [Smaug-72B-v0.1](https://huggingface.co/abacusai/Smaug-72B-v0.1).
<!-- description end -->
<!-- README_GGUF.md-about-gguf s... | {"license": "other", "tags": ["GGUF"], "base_model": "moreh/MoMo-72B-lora-1.8.7-DPO", "license_name": "tongyi-qianwen-license-agreement", "license_link": "https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT", "quantized_by": "andrijdavid"} | LiteLLMs/Smaug-72B-v0.1-GGUF | null | [
"GGUF",
"arxiv:2402.13228",
"base_model:moreh/MoMo-72B-lora-1.8.7-DPO",
"license:other",
"region:us"
] | null | 2024-04-29T23:25:46+00:00 | [
"2402.13228"
] | [] | TAGS
#GGUF #arxiv-2402.13228 #base_model-moreh/MoMo-72B-lora-1.8.7-DPO #license-other #region-us
| Smaug-72B-v0.1-GGUF
===================
* Original model: Smaug-72B-v0.1
Description
-----------
This repo contains GGUF format model files for Smaug-72B-v0.1.
### About GGUF
GGUF is a new format introduced by the URL team on August 21st 2023. It is a replacement for GGML, which is no longer supported by URL.... | [
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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_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_3-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_3-seqsight_16384_512_34M-L8_f | null | [
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"safetensors",
"generated_from_trainer",
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] | null | 2024-04-29T23:27:30+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_3-seqsight\_16384\_512\_34M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8517
* F1 Score: 0.8452
* A... | [
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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": []} | lunarsylph/stablecell_v53 | null | [
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"safetensors",
"stablelm",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-29T23:27:44+00:00 | [
"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.
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- Funded by [optional]:
- Shared by [optional]:
- Model type:
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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_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_3-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_3-seqsight_16384_512_34M-L32_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_3-seqsight\_16384\_512\_34M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8282
* F1 Score: 0.8534
*... | [
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null | transformers | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/Hugosh71/Llama-3-8B-Eden
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl", "sft"], "base_model": "Hugosh71/Llama-3-8B-Eden", "quantized_by": "mradermacher"} | mradermacher/Llama-3-8B-Eden-GGUF | null | [
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"license:apache-2.0",
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"en"
] | TAGS
#transformers #gguf #text-generation-inference #unsloth #llama #trl #sft #en #base_model-Hugosh71/Llama-3-8B-Eden #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... | [] | [
"TAGS\n#transformers #gguf #text-generation-inference #unsloth #llama #trl #sft #en #base_model-Hugosh71/Llama-3-8B-Eden #license-apache-2.0 #endpoints_compatible #region-us \n"
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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": []} | shallow6414/7aeerbr | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-29T23:29:15+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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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_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_2-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_2-seqsight_16384_512_34M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:29:29+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_2-seqsight\_16384\_512\_34M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4898
* F1 Score: 0.8627
* 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_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_2-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_2-seqsight_16384_512_34M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:29:29+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_2-seqsight\_16384\_512\_34M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2431
* F1 Score: 0.8933
* 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_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_mouse_2-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_2-seqsight_16384_512_34M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:29:58+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_mouse\_2-seqsight\_16384\_512\_34M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_mouse\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5170
* F1 Score: 0.8719
*... | [
"### 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 | null |
## Llamacpp imatrix Quantizations of NPC-LLM-3_8B
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2756">b2756</a> for quantization.
Original model: https://huggingface.co/Gigax/NPC-LLM-3_8B
All quants made using imatrix opti... | {"language": ["en"], "license": "mit", "quantized_by": "bartowski", "pipeline_tag": "text-generation"} | bartowski/NPC-LLM-3_8B-GGUF | null | [
"gguf",
"text-generation",
"en",
"license:mit",
"region:us"
] | null | 2024-04-29T23:31:09+00:00 | [] | [
"en"
] | TAGS
#gguf #text-generation #en #license-mit #region-us
| Llamacpp imatrix Quantizations of NPC-LLM-3\_8B
-----------------------------------------------
Using <a href="URL release <a href="URL for quantization.
Original model: URL
All quants made using imatrix option with dataset provided by Kalomaze here
Prompt format
-------------
Download a file (not the whole b... | [] | [
"TAGS\n#gguf #text-generation #en #license-mit #region-us \n"
] | [
19
] | [
"TAGS\n#gguf #text-generation #en #license-mit #region-us \n"
] |
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": "t5-base"} | PQlet/T5base-lora-sumarizationTables-v2-MLM-lambda0.01 | null | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:t5-base",
"region:us"
] | null | 2024-04-29T23:32:45+00:00 | [
"1910.09700"
] | [] | TAGS
#peft #safetensors #arxiv-1910.09700 #base_model-t5-base #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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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_34M-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_34M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_16384_512_34M-L8_f | null | [
"peft",
"safetensors",
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"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_splice\_reconstructed-seqsight\_16384\_512\_34M-L8\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed dataset.
It achieves the following results on the evaluation set:
... | [
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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_34M-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_34M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_16384_512_34M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:33:25+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_splice\_reconstructed-seqsight\_16384\_512\_34M-L1\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed dataset.
It achieves the following results on the evaluation set:
... | [
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token-classification | span-marker |
# SpanMarker with roberta-large on Jerado/enron_intangibles_ner
This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model trained on the [Jerado/enron_intangibles_ner](https://huggingface.co/datasets/Jerado/enron_intangibles_ner) dataset that can be used for Named Entity Recognition. This SpanMarker mo... | {"language": ["en"], "license": "apache-2.0", "library_name": "span-marker", "tags": ["span-marker", "token-classification", "ner", "named-entity-recognition", "generated_from_span_marker_trainer"], "datasets": ["Jerado/enron_intangibles_ner"], "metrics": ["precision", "recall", "f1"], "base_model": "roberta-large", "w... | Jerado/span-marker-roberta-large-enron | null | [
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"base_model:roberta-large",
"license:apache-2.0",
"model-index",
"region:us"
] | null | 2024-04-29T23:34:21+00:00 | [] | [
"en"
] | TAGS
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| SpanMarker with roberta-large on Jerado/enron\_intangibles\_ner
===============================================================
This is a SpanMarker model trained on the Jerado/enron\_intangibles\_ner dataset that can be used for Named Entity Recognition. This SpanMarker model uses roberta-large as the underlying enc... | [
"### Model Description\n\n\n* Model Type: SpanMarker\n* Encoder: roberta-large\n* Maximum Sequence Length: 256 tokens\n* Maximum Entity Length: 6 words\n* Training Dataset: Jerado/enron\\_intangibles\\_ner\n* Language: en\n* License: apache-2.0",
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"TAGS\n#span-marker #tensorboard #safetensors #token-classification #ner #named-entity-recognition #generated_from_span_marker_trainer #en #dataset-Jerado/enron_intangibles_ner #base_model-roberta-large #license-apache-2.0 #model-index #region-us \n### Model Description\n\n\n* Model Type: SpanMarker\n* Encoder: rob... |
image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-patch16-224-in21k-finetuned
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingfa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["image_folder"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "vit-base-patch16-224-in21k-finetuned", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, ... | motheecreator/vit-base-patch16-224-in21k-finetuned | null | [
"transformers",
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"safetensors",
"vit",
"image-classification",
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"license:apache-2.0",
"model-index",
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] | null | 2024-04-29T23:34:51+00:00 | [] | [] | TAGS
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| vit-base-patch16-224-in21k-finetuned
====================================
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the image\_folder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9803
* Accuracy: 0.7058
Model description
-----------------
More info... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0428HMA4
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset.... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0428HMA4", "results": []}]} | Litzy619/O0428HMA4 | null | [
"safetensors",
"generated_from_trainer",
"base_model:allenai/OLMo-1B",
"license:apache-2.0",
"region:us"
] | null | 2024-04-29T23:36:26+00:00 | [] | [] | TAGS
#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0428HMA4
=========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1449
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0428HMA5
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset.... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0428HMA5", "results": []}]} | Litzy619/O0428HMA5 | null | [
"safetensors",
"generated_from_trainer",
"base_model:allenai/OLMo-1B",
"license:apache-2.0",
"region:us"
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#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0428HMA5
=========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1828
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More 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_splice_reconstructed-seqsight_16384_512_34M-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_34M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_16384_512_34M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
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] | null | 2024-04-29T23:37:38+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_splice\_reconstructed-seqsight\_16384\_512\_34M-L32\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed dataset.
It achieves the following results on the evaluation set... | [
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... | [
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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_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_tf_0-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_16384_512_34M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:38:32+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_tf\_0-seqsight\_16384\_512\_34M-L1\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3880
* F1 Score: 0.8258
* 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_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_tf_0-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_16384_512_34M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:39:27+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_tf\_0-seqsight\_16384\_512\_34M-L8\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3833
* F1 Score: 0.8273
* 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_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_tf_1-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_16384_512_34M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:39:33+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_tf\_1-seqsight\_16384\_512\_34M-L1\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3443
* F1 Score: 0.8566
* 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_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_tf_0-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_16384_512_34M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:39:33+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_tf\_0-seqsight\_16384\_512\_34M-L32\_f
===========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3839
* F1 Score: 0.8256
* 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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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. -->
# output_dir
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) o... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "microsoft/deberta-v3-base", "model-index": [{"name": "output_dir", "results": []}]} | tralon/test-1 | null | [
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"region:us"
] | null | 2024-04-29T23:40:13+00:00 | [] | [] | TAGS
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|
# output_dir
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0625
- F Beta Score: 0.9639
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and ... | [
"# output_dir\n\nThis model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset.\nIt achieves the following results on the evaluation set:\n- Loss: 0.0625\n- F Beta Score: 0.9639",
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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_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_tf_1-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_16384_512_34M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:41:03+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_tf\_1-seqsight\_16384\_512\_34M-L8\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3442
* F1 Score: 0.8604
* 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",
... | [
"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us \n",
"### 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* ... | [
42,
100,
5,
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"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us \n### 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* optimi... |
null | transformers | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/tanyakansal/WizardLM-Mistral-CodeLlama-7b
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If th... | {"language": ["en"], "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": "tanyakansal/WizardLM-Mistral-CodeLlama-7b", "quantized_by": "mradermacher"} | mradermacher/WizardLM-Mistral-CodeLlama-7b-GGUF | null | [
"transformers",
"gguf",
"mergekit",
"merge",
"en",
"base_model:tanyakansal/WizardLM-Mistral-CodeLlama-7b",
"endpoints_compatible",
"region:us"
] | null | 2024-04-29T23:41:45+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #mergekit #merge #en #base_model-tanyakansal/WizardLM-Mistral-CodeLlama-7b #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
"TAGS\n#transformers #gguf #mergekit #merge #en #base_model-tanyakansal/WizardLM-Mistral-CodeLlama-7b #endpoints_compatible #region-us \n"
] | [
44
] | [
"TAGS\n#transformers #gguf #mergekit #merge #en #base_model-tanyakansal/WizardLM-Mistral-CodeLlama-7b #endpoints_compatible #region-us \n"
] |
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_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_tf_1-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_16384_512_34M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T23:41:58+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_tf\_1-seqsight\_16384\_512\_34M-L32\_f
===========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3537
* F1 Score: 0.8534
* 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",
... | [
"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us \n",
"### 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* ... | [
42,
100,
5,
52
] | [
"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us \n### 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* optimi... |
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