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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This is llama3 8b family chat model finetuned from base [`epfl-llm/meditron-7b`](https://huggingface.co/epfl-llm/meditron-7b) with [open assist dataset](https://huggingface.co/datasets/mlabonne/guanaco-llama2) using SFT [QLora](htt... | {"license": "apache-2.0", "library_name": "transformers", "tags": ["medical"], "datasets": ["skumar9/orpo-mmlu"]} | skumar9/Llama-medx_v2 | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"medical",
"conversational",
"dataset:skumar9/orpo-mmlu",
"arxiv:2305.14314",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-29T20:49:25+00:00 | [
"2305.14314"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #medical #conversational #dataset-skumar9/orpo-mmlu #arxiv-2305.14314 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
This is llama3 8b family chat model finetuned from base 'epfl-llm/meditron-7b' with open assist dataset using SFT QLora .<br>
All the linear parameters were made trainable with a rank of 16.<br>
# Prompt template: Llama
# Usage:
| [
"# Model Card for Model ID\n\n\n\nThis is llama3 8b family chat model finetuned from base 'epfl-llm/meditron-7b' with open assist dataset using SFT QLora .<br>\nAll the linear parameters were made trainable with a rank of 16.<br>",
"# Prompt template: Llama",
"# Usage:"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #medical #conversational #dataset-skumar9/orpo-mmlu #arxiv-2305.14314 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Model Card for Model ID\n\n\n\nThis is llama3 8b family chat model finetuned... | [
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"TAGS\n#transformers #safetensors #llama #text-generation #medical #conversational #dataset-skumar9/orpo-mmlu #arxiv-2305.14314 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Model Card for Model ID\n\n\n\nThis is llama3 8b family chat model finetuned from ... |
text-to-image | null |
# Cos Stable Diffusion XL 1.0 and Cos Stable Diffusion XL 1.0 Edit
Cos Stable Diffusion XL 1.0 Base is tuned to use a Cosine-Continuous EDM VPred schedule. The most notable feature of this schedule change is its capacity to produce the full color range from pitch black to pure white, alongside more subtle improvement... | {"license": "other", "pipeline_tag": "text-to-image", "license_name": "cosxl-nc-community", "license_link": "LICENSE", "extra_gated_prompt": "STABILITY AI NON-COMMERCIAL RESEARCH COMMUNITY LICENSE AGREEMENT\t Dated: April 7th, 2024\nBy clicking \u201cI Accept\u201d below or by using or distributing any portion or eleme... | TIGER-Lab/cosxl | null | [
"text-to-image",
"license:other",
"region:us",
"has_space"
] | null | 2024-04-29T20:51:49+00:00 | [] | [] | TAGS
#text-to-image #license-other #region-us #has_space
|
# Cos Stable Diffusion XL 1.0 and Cos Stable Diffusion XL 1.0 Edit
Cos Stable Diffusion XL 1.0 Base is tuned to use a Cosine-Continuous EDM VPred schedule. The most notable feature of this schedule change is its capacity to produce the full color range from pitch black to pure white, alongside more subtle improvement... | [
"# Cos Stable Diffusion XL 1.0 and Cos Stable Diffusion XL 1.0 Edit\n\nCos Stable Diffusion XL 1.0 Base is tuned to use a Cosine-Continuous EDM VPred schedule. The most notable feature of this schedule change is its capacity to produce the full color range from pitch black to pure white, alongside more subtle impro... | [
"TAGS\n#text-to-image #license-other #region-us #has_space \n",
"# Cos Stable Diffusion XL 1.0 and Cos Stable Diffusion XL 1.0 Edit\n\nCos Stable Diffusion XL 1.0 Base is tuned to use a Cosine-Continuous EDM VPred schedule. The most notable feature of this schedule change is its capacity to produce the full color... | [
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3,
29
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"TAGS\n#text-to-image #license-other #region-us #has_space \n# Cos Stable Diffusion XL 1.0 and Cos Stable Diffusion XL 1.0 Edit\n\nCos Stable Diffusion XL 1.0 Base is tuned to use a Cosine-Continuous EDM VPred schedule. The most notable feature of this schedule change is its capacity to produce the full color range... |
null | transformers | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/Yuma42/KangalKhan-RawRuby-7B
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/KangalKhan-R... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["merge", "mergekit", "lazymergekit", "Yuma42/KangalKhan-Ruby-7B-Fixed", "Yuma42/KangalKhan-RawEmerald-7B"], "base_model": "Yuma42/KangalKhan-RawRuby-7B", "quantized_by": "mradermacher"} | mradermacher/KangalKhan-RawRuby-7B-i1-GGUF | null | [
"transformers",
"gguf",
"merge",
"mergekit",
"lazymergekit",
"Yuma42/KangalKhan-Ruby-7B-Fixed",
"Yuma42/KangalKhan-RawEmerald-7B",
"en",
"base_model:Yuma42/KangalKhan-RawRuby-7B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-29T20:54:36+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #merge #mergekit #lazymergekit #Yuma42/KangalKhan-Ruby-7B-Fixed #Yuma42/KangalKhan-RawEmerald-7B #en #base_model-Yuma42/KangalKhan-RawRuby-7B #license-apache-2.0 #endpoints_compatible #region-us
| About
-----
weighted/imatrix quants of URL
static quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
"TAGS\n#transformers #gguf #merge #mergekit #lazymergekit #Yuma42/KangalKhan-Ruby-7B-Fixed #Yuma42/KangalKhan-RawEmerald-7B #en #base_model-Yuma42/KangalKhan-RawRuby-7B #license-apache-2.0 #endpoints_compatible #region-us \n"
] | [
86
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"TAGS\n#transformers #gguf #merge #mergekit #lazymergekit #Yuma42/KangalKhan-Ruby-7B-Fixed #Yuma42/KangalKhan-RawEmerald-7B #en #base_model-Yuma42/KangalKhan-RawRuby-7B #license-apache-2.0 #endpoints_compatible #region-us \n"
] |
text-generation | transformers |
# mlx-community/starcoder2-15b-instruct-v0.1-4bit
This model was converted to MLX format from [`bigcode/starcoder2-15b-instruct-v0.1`]() using mlx-lm version **0.10.0**.
Refer to the [original model card](https://huggingface.co/bigcode/starcoder2-15b-instruct-v0.1) for more details on the model.
## Use with mlx
```ba... | {"license": "bigcode-openrail-m", "library_name": "transformers", "tags": ["code", "mlx"], "datasets": ["bigcode/self-oss-instruct-sc2-exec-filter-50k"], "base_model": "bigcode/starcoder2-15b", "pipeline_tag": "text-generation", "model-index": [{"name": "starcoder2-15b-instruct-v0.1", "results": [{"task": {"type": "tex... | mlx-community/starcoder2-15b-instruct-v0.1-4bit | null | [
"transformers",
"safetensors",
"starcoder2",
"text-generation",
"code",
"mlx",
"conversational",
"dataset:bigcode/self-oss-instruct-sc2-exec-filter-50k",
"base_model:bigcode/starcoder2-15b",
"license:bigcode-openrail-m",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-... | null | 2024-04-29T20:55:58+00:00 | [] | [] | TAGS
#transformers #safetensors #starcoder2 #text-generation #code #mlx #conversational #dataset-bigcode/self-oss-instruct-sc2-exec-filter-50k #base_model-bigcode/starcoder2-15b #license-bigcode-openrail-m #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# mlx-community/starcoder2-15b-instruct-v0.1-4bit
This model was converted to MLX format from ['bigcode/starcoder2-15b-instruct-v0.1']() using mlx-lm version 0.10.0.
Refer to the original model card for more details on the model.
## Use with mlx
| [
"# mlx-community/starcoder2-15b-instruct-v0.1-4bit\nThis model was converted to MLX format from ['bigcode/starcoder2-15b-instruct-v0.1']() using mlx-lm version 0.10.0.\nRefer to the original model card for more details on the model.",
"## Use with mlx"
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_tata-seqsight_16384_512_34M-L32_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_prom_prom_300_tata-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_16384_512_34M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T20:55:58+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_16384\_512\_34M-L32\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_tata dataset.
It achieves the following results on the evaluation set... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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"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 | 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_prom_prom_300_notata-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_prom_prom_300_notata-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-seqsight_16384_512_34M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T20:55:58+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_prom\_prom\_300\_notata-seqsight\_16384\_512\_34M-L1\_f
============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_notata dataset.
It achieves the following results on the evaluation... | [
"### 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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"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 | 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_prom_prom_300_tata-seqsight_16384_512_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_3... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_16384_512_34M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T20:55:58+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_16384\_512\_34M-L1\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_tata dataset.
It achieves the following results on the evaluation set:
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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"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 | 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_prom_prom_300_tata-seqsight_16384_512_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_3... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_16384_512_34M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T20:55:58+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_16384\_512\_34M-L8\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_tata dataset.
It achieves the following results on the evaluation set:
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* ... | [
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"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 | 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_prom_prom_core_all-seqsight_16384_512_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_3... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_prom_prom_core_all-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_all-seqsight_16384_512_34M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T20:55:58+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_prom\_prom\_core\_all-seqsight\_16384\_512\_34M-L1\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_all dataset.
It achieves the following results on the evaluation set:
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* ... | [
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"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 | 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_prom_prom_300_notata-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_prom_prom_300_notata-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-seqsight_16384_512_34M-L8_f | null | [
"peft",
"safetensors",
"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\_prom\_prom\_300\_notata-seqsight\_16384\_512\_34M-L8\_f
============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_notata dataset.
It achieves the following results on the evaluation... | [
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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_prom_prom_300_notata-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_prom_prom_300_notata-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-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\_prom\_prom\_300\_notata-seqsight\_16384\_512\_34M-L32\_f
=============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_notata dataset.
It achieves the following results on the evaluati... | [
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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_prom_prom_core_all-seqsight_16384_512_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_3... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_prom_prom_core_all-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_all-seqsight_16384_512_34M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T20:55:58+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_prom\_prom\_core\_all-seqsight\_16384\_512\_34M-L8\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_all dataset.
It achieves the following results on the evaluation set:
... | [
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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. -->
# rubra-9.5b-yaml_v1
This model is a fine-tuned version of [models/rubra-9.5b-base](https://huggingface.co/models/rubra-9.5b-base)... | {"license": "other", "tags": ["llama-factory", "freeze", "generated_from_trainer"], "base_model": "models/rubra-9.5b-base", "model-index": [{"name": "rubra-9.5b-yaml_v1", "results": []}]} | sanjay920/mistral-9.5-fc-yaml-v1 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"llama-factory",
"freeze",
"generated_from_trainer",
"conversational",
"base_model:models/rubra-9.5b-base",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-29T20:56:01+00:00 | [] | [] | TAGS
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|
# rubra-9.5b-yaml_v1
This model is a fine-tuned version of models/rubra-9.5b-base on the yaml-simple, the yaml-multiple, the yaml-parallel, the yaml-parallel_multiple, the yaml-relevance, the yaml-sql, the yaml-rest, the yaml-gptscript-x8 and the yaml-chain_of_function datasets.
## Model description
More informat... | [
"# rubra-9.5b-yaml_v1\n\nThis model is a fine-tuned version of models/rubra-9.5b-base on the yaml-simple, the yaml-multiple, the yaml-parallel, the yaml-parallel_multiple, the yaml-relevance, the yaml-sql, the yaml-rest, the yaml-gptscript-x8 and the yaml-chain_of_function datasets.",
"## Model description\n\nMor... | [
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text-generation | transformers |
# mlx-community/starcoder2-15b-instruct-v0.1-8bit
This model was converted to MLX format from [`bigcode/starcoder2-15b-instruct-v0.1`]() using mlx-lm version **0.10.0**.
Refer to the [original model card](https://huggingface.co/bigcode/starcoder2-15b-instruct-v0.1) for more details on the model.
## Use with mlx
```ba... | {"license": "bigcode-openrail-m", "library_name": "transformers", "tags": ["code", "mlx"], "datasets": ["bigcode/self-oss-instruct-sc2-exec-filter-50k"], "base_model": "bigcode/starcoder2-15b", "pipeline_tag": "text-generation", "model-index": [{"name": "starcoder2-15b-instruct-v0.1", "results": [{"task": {"type": "tex... | mlx-community/starcoder2-15b-instruct-v0.1-8bit | null | [
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"base_model:bigcode/starcoder2-15b",
"license:bigcode-openrail-m",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-... | null | 2024-04-29T20:56:08+00:00 | [] | [] | TAGS
#transformers #safetensors #starcoder2 #text-generation #code #mlx #conversational #dataset-bigcode/self-oss-instruct-sc2-exec-filter-50k #base_model-bigcode/starcoder2-15b #license-bigcode-openrail-m #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# mlx-community/starcoder2-15b-instruct-v0.1-8bit
This model was converted to MLX format from ['bigcode/starcoder2-15b-instruct-v0.1']() using mlx-lm version 0.10.0.
Refer to the original model card for more details on the model.
## Use with mlx
| [
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null | transformers | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/yzhuang/Meta-Llama-3-8B-Instruct_fictional_arc_Japanese_v1
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at... | {"language": ["en"], "license": "other", "library_name": "transformers", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "yzhuang/Meta-Llama-3-8B-Instruct_fictional_arc_Japanese_v1", "quantized_by": "mradermacher"} | mradermacher/Meta-Llama-3-8B-Instruct_fictional_arc_Japanese_v1-GGUF | null | [
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"base_model:yzhuang/Meta-Llama-3-8B-Instruct_fictional_arc_Japanese_v1",
"license:other",
"endpoints_compatible",
"region:us"
] | null | 2024-04-29T20:58:24+00:00 | [] | [
"en"
] | TAGS
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| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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] |
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/ak3iih5 | null | [
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"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-29T20:58:25+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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sentence-similarity | sentence-transformers |
# sergeyvi4ev/all-MiniLM-ragsql-code
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this mo... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "datasets": ["sergeyvi4ev/sql_questions_triplets"], "pipeline_tag": "sentence-similarity"} | sergeyvi4ev/all-MiniLM-RAGSQL-code | null | [
"sentence-transformers",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"dataset:sergeyvi4ev/sql_questions_triplets",
"endpoints_compatible",
"region:us"
] | null | 2024-04-29T21:00:17+00:00 | [] | [] | TAGS
#sentence-transformers #safetensors #bert #feature-extraction #sentence-similarity #dataset-sergeyvi4ev/sql_questions_triplets #endpoints_compatible #region-us
|
# sergeyvi4ev/all-MiniLM-ragsql-code
This is a sentence-transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-transformers instal... | [
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null | transformers | # Llama-3-Smaug-8B-GGUF
- Original model: [Llama-3-Smaug-8B](https://huggingface.co/abacusai/Llama-3-Smaug-8B)
<!-- description start -->
## Description
This repo contains GGUF format model files for [Llama-3-Smaug-8B](https://huggingface.co/abacusai/Llama-3-Smaug-8B).
<!-- description end -->
<!-- README_GGUF.md-ab... | {"license": "llama2", "library_name": "transformers", "tags": ["GGUF"], "datasets": ["aqua_rat", "microsoft/orca-math-word-problems-200k", "m-a-p/CodeFeedback-Filtered-Instruction", "anon8231489123/ShareGPT_Vicuna_unfiltered"], "quantized_by": "andrijdavid"} | LiteLLMs/Llama-3-Smaug-8B-GGUF | null | [
"transformers",
"gguf",
"GGUF",
"dataset:aqua_rat",
"dataset:microsoft/orca-math-word-problems-200k",
"dataset:m-a-p/CodeFeedback-Filtered-Instruction",
"dataset:anon8231489123/ShareGPT_Vicuna_unfiltered",
"arxiv:2402.13228",
"license:llama2",
"endpoints_compatible",
"region:us"
] | null | 2024-04-29T21:00:25+00:00 | [
"2402.13228"
] | [] | TAGS
#transformers #gguf #GGUF #dataset-aqua_rat #dataset-microsoft/orca-math-word-problems-200k #dataset-m-a-p/CodeFeedback-Filtered-Instruction #dataset-anon8231489123/ShareGPT_Vicuna_unfiltered #arxiv-2402.13228 #license-llama2 #endpoints_compatible #region-us
| # Llama-3-Smaug-8B-GGUF
- Original model: Llama-3-Smaug-8B
## Description
This repo contains GGUF format model files for Llama-3-Smaug-8B.
### 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.
Here is an incomplete li... | [
"# Llama-3-Smaug-8B-GGUF\n- Original model: Llama-3-Smaug-8B",
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null | transformers |
# Uploaded model
- **Developed by:** nicorprofe
- **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/unslot... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | nicorprofe/llama3-8b-oig-unsloth-merged | null | [
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"llama",
"trl",
"en",
"base_model:unsloth/llama-3-8b-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-29T21:00:41+00:00 | [] | [
"en"
] | TAGS
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|
# Uploaded model
- Developed by: nicorprofe
- 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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null | transformers | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/Azazelle/Llama-3-8B-Help-Me
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show... | {"language": ["en"], "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": "Azazelle/Llama-3-8B-Help-Me", "quantized_by": "mradermacher"} | mradermacher/Llama-3-8B-Help-Me-GGUF | null | [
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#transformers #gguf #mergekit #merge #en #base_model-Azazelle/Llama-3-8B-Help-Me #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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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. -->
# QA_FineTuned_AraElectra
This model is a fine-tuned version of [aubmindlab/araelectra-base-generator](https://huggingface.co/aubm... | {"language": ["ar"], "tags": ["generated_from_trainer"], "base_model": "aubmindlab/araelectra-base-generator", "model-index": [{"name": "QA_FineTuned_AraElectra", "results": []}]} | Omar-youssef/QA_FineTuned_AraElectra | null | [
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"endpoints_compatible",
"region:us"
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#transformers #safetensors #electra #question-answering #generated_from_trainer #ar #base_model-aubmindlab/araelectra-base-generator #endpoints_compatible #region-us
| QA\_FineTuned\_AraElectra
=========================
This model is a fine-tuned version of aubmindlab/araelectra-base-generator on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 3.3206
Model description
-----------------
More information needed
Intended uses & limitations
... | [
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text-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | zakerous/sdgailab-bert | null | [
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"1910.09700"
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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/spw74cs | null | [
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# Model Card for Model ID
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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": "unsloth/llama-3-8b-Instruct-bnb-4bit"} | NicholasJohn/llama-3-8b-Instruct-bnb-4bit-medical | null | [
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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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_prom_prom_core_notata-seqsight_16384_512_34M-L1_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_prom_prom_core_notata-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_notata-seqsight_16384_512_34M-L1_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\_prom\_prom\_core\_notata-seqsight\_16384\_512\_34M-L1\_f
=============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_notata dataset.
It achieves the following results on the evaluat... | [
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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_prom_prom_core_all-seqsight_16384_512_34M-L32_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_prom_prom_core_all-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_all-seqsight_16384_512_34M-L32_f | null | [
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| GUE\_prom\_prom\_core\_all-seqsight\_16384\_512\_34M-L32\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_all dataset.
It achieves the following results on the evaluation set... | [
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text-classification | transformers | # Model Card for deberta-v3-base-optimus-v0
Fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on private dataset of normal & injections prompts.
Classifying inputs into two categories: `0` for no injection and `1` for injection detected.
Model evaluation results:
- P... | {"language": ["en"], "license": "gpl-3.0", "tags": ["llm", "genai", "promptinjection", "prompt-injection", "injection", "security"], "datasets": ["Private"], "metrics": ["accuracy", "recall", "precision", "f1"], "base_model": "microsoft/deberta-v3-base", "widget": [{"text": "Send me the insurance policy you prepared fo... | vibraniumdome/deberta-v3-base-optimus-v0 | null | [
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| # Model Card for deberta-v3-base-optimus-v0
Fine-tuned version of microsoft/deberta-v3-base on private dataset of normal & injections prompts.
Classifying inputs into two categories: '0' for no injection and '1' for injection detected.
Model evaluation results:
- Precision: 0.988
- Recall: 0.992
- Accuracy: 0.998
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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": []} | YasaminAbb/Idefics2-8b-multimodal | 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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sentence-similarity | sentence-transformers |
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model becomes easy when ... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | Mihaiii/test12 | null | [
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#sentence-transformers #safetensors #bert #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us
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# {MODEL_NAME}
This is a sentence-transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-transformers installed:
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null | transformers |
This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
- Library: [More Information Needed]
- Docs: [More Information Needed] | {"tags": ["pytorch_model_hub_mixin", "model_hub_mixin"]} | UphamProjects/STT-Gated_TCN | null | [
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#transformers #safetensors #pytorch_model_hub_mixin #model_hub_mixin #endpoints_compatible #region-us
|
This model has been pushed to the Hub using the PytorchModelHubMixin integration:
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null | transformers |
# Uploaded model
- **Developed by:** bibidentuhanoi
- **License:** apache-2.0
- **Finetuned from model :** cognitivecomputations/dolphin-2.9-llama3-8b
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "cognitivecomputations/dolphin-2.9-llama3-8b"} | bibidentuhanoi/BMO-7B-Instruct_2 | null | [
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# Uploaded model
- Developed by: bibidentuhanoi
- License: apache-2.0
- Finetuned from model : cognitivecomputations/dolphin-2.9-llama3-8b
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# large-plain
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It ... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "roberta-base", "model-index": [{"name": "large-plain", "results": []}]} | mhr2004/large-plain | null | [
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| large-plain
===========
This model is a fine-tuned version of roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8970
* Accuracy: 0.4756
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
Mor... | [
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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": "t5-base"} | PQlet/T5base-lora-sumarizationTables-v2-MLM-lambda0.001 | null | [
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- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
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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_prom_prom_core_notata-seqsight_16384_512_34M-L8_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_prom_prom_core_notata-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_notata-seqsight_16384_512_34M-L8_f | null | [
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| GUE\_prom\_prom\_core\_notata-seqsight\_16384\_512\_34M-L8\_f
=============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_notata dataset.
It achieves the following results on the evaluat... | [
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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_prom_prom_core_notata-seqsight_16384_512_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_5... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_prom_prom_core_notata-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_notata-seqsight_16384_512_34M-L32_f | null | [
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| GUE\_prom\_prom\_core\_notata-seqsight\_16384\_512\_34M-L32\_f
==============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_notata dataset.
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text-generation | transformers | base model = beomi-Llama-3-Open-Ko-8B-Instruct-preview
base model = hansoldeco-beomi-Llama-3-Open-Ko-8B-Instruct-preview (Trained via Axolotl)
dora_train config
(from fsdp_qlora repo)
```
export CUDA_VISIBLE_DEVICES=0,1
python train.py \
--train_type bnb_dora \
--model_name sosoai/hansoldeco-beomi-Llama-3-Open-Ko-8B-... | {} | sosoai/hansoldeco-beomi-Llama-3-Open-Ko-8B-Instruct-preview-qdora-v0.1 | null | [
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| base model = beomi-Llama-3-Open-Ko-8B-Instruct-preview
base model = hansoldeco-beomi-Llama-3-Open-Ko-8B-Instruct-preview (Trained via Axolotl)
dora_train config
(from fsdp_qlora repo)
Dataset = hansoldeco domain own dataset (Non open)
Dataset = kuotient/orca-math-word-problems-193k-korean
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null | null | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
... | {"tags": ["pruna-ai"], "metrics": ["memory_disk", "memory_inference", "inference_latency", "inference_throughput", "inference_CO2_emissions", "inference_energy_consumption"], "thumbnail": "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"} | PrunaAI/Llama-3-8B-Instruct-Gradient-1048k-GGUF-smashed | null | [
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#gguf #pruna-ai #region-us
|
[](URL target=)
![Twitter](URL
![GitHub](URL
![LinkedIn](URL
![Discord](URL
This repo contains GGUF versions of the gradientai/Llama-3-8B-Instruct-Gradient-1048k model.
--------------------------------------------------------------------------------------------
Simply make AI models cheaper... | [
"### How to load this model in Python code, using llama-cpp-python\n\nFor full documentation, please see: llama-cpp-python docs.",
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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_prom_prom_core_tata-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_prom_prom_core_tata-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_tata-seqsight_16384_512_34M-L8_f | null | [
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| GUE\_prom\_prom\_core\_tata-seqsight\_16384\_512\_34M-L8\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_tata dataset.
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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_prom_prom_core_tata-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_prom_prom_core_tata-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_tata-seqsight_16384_512_34M-L1_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\_prom\_prom\_core\_tata-seqsight\_16384\_512\_34M-L1\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_tata dataset.
It achieves the following results on the evaluation se... | [
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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_prom_prom_core_tata-seqsight_16384_512_34M-L32_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_prom_prom_core_tata-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_tata-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\_prom\_prom\_core\_tata-seqsight\_16384\_512\_34M-L32\_f
============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_tata dataset.
It achieves the following results on the evaluation ... | [
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null | fastai |
# Amazing!
🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([docume... | {"tags": ["fastai"]} | rahaiduc/paisajes | null | [
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# Amazing!
Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the documentation here)!
2. Create a demo in Gradio or Streamlit using Spaces (documentation here).
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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_prom_prom_300_all-seqsight_16384_512_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_prom_prom_300_all-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_all-seqsight_16384_512_34M-L1_f | null | [
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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\_prom\_prom\_300\_all-seqsight\_16384\_512\_34M-L1\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_all 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_prom_prom_300_all-seqsight_16384_512_34M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_3... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_prom_prom_300_all-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_all-seqsight_16384_512_34M-L32_f | null | [
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| GUE\_prom\_prom\_300\_all-seqsight\_16384\_512\_34M-L32\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_all 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_prom_prom_300_all-seqsight_16384_512_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_prom_prom_300_all-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_all-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\_prom\_prom\_300\_all-seqsight\_16384\_512\_34M-L8\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_all dataset.
It achieves the following results on the evaluation set:
*... | [
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sentence-similarity | sentence-transformers |
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model becomes easy when ... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | Mihaiii/test13 | null | [
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|
# {MODEL_NAME}
This is a sentence-transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
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null | null | LoRA extraction from Gradient AI's https://huggingface.co/gradientai/Llama-3-8B-Instruct-Gradient-1048k model.
LoRA extraction only targeted from the self_attn modules.
Rank: 1024 | {} | winglian/llama-3-1m-context-gradient-lora | null | [
"safetensors",
"region:us"
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#safetensors #region-us
| LoRA extraction from Gradient AI's URL model.
LoRA extraction only targeted from the self_attn modules.
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null | transformers | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/giux78/llama3-8B-usenet-merged
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not s... | {"language": ["en"], "library_name": "transformers", "tags": [], "base_model": "giux78/llama3-8B-usenet-merged", "quantized_by": "mradermacher"} | mradermacher/llama3-8B-usenet-merged-GGUF | null | [
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#transformers #gguf #en #base_model-giux78/llama3-8B-usenet-merged #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
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If you are unsure how to use GGUF file... | [] | [
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - embracellm/sushi04_LoRA
<Gallery />
## Model description
These are embracellm/sushi04_LoRA LoR... | {"license": "openrail++", "library_name": "diffusers", "tags": ["text-to-image", "text-to-image", "diffusers-training", "diffusers", "dora", "template:sd-lora", "stable-diffusion-xl", "stable-diffusion-xl-diffusers"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "a photo of sushi", "widg... | embracellm/sushi04_LoRA | null | [
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"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"region:us"
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|
# SDXL LoRA DreamBooth - embracellm/sushi04_LoRA
<Gallery />
## Model description
These are embracellm/sushi04_LoRA LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | lunarsylph/mooncell_v32 | null | [
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"autotrain_compatible",
"endpoints_compatible",
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"region:us"
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"1910.09700"
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# DistilGPT2-model
This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co/distilbert/distilgpt2) on ... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "distilbert/distilgpt2", "model-index": [{"name": "DistilGPT2-model", "results": []}]} | anushkat/DistilGPT2-model | null | [
"peft",
"safetensors",
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"base_model:distilbert/distilgpt2",
"license:apache-2.0",
"region:us"
] | null | 2024-04-29T21:24:14+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-distilbert/distilgpt2 #license-apache-2.0 #region-us
| DistilGPT2-model
================
This model is a fine-tuned version of distilbert/distilgpt2 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 2.2126
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More ... | [
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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_H3K14ac-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_H3K14ac-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_16384_512_34M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T21:24:41+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_16384\_512\_34M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4929
* 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_H3K14ac-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_H3K14ac-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_16384_512_34M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T21:24:41+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_16384\_512\_34M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4869
* 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_H3K4me2-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_H3K4me2-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me2-seqsight_16384_512_34M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T21:24:41+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3K4me2-seqsight\_16384\_512\_34M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6031
* 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_H3K14ac-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_H3K14ac-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_16384_512_34M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T21:24:41+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_16384\_512\_34M-L32\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4977
* 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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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": []} | armaniii/llama-3-8b-claim-topic-extraction | null | [
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|
# Model Card for Model ID
## Model Details
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | peft |
<!-- 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_H3K4me2-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_H3K4me2-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me2-seqsight_16384_512_34M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_34M",
"region:us"
] | null | 2024-04-29T21:25:02+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_34M #region-us
| GUE\_EMP\_H3K4me2-seqsight\_16384\_512\_34M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6299
* 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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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": []} | andersonbcdefg/tiny-emb-2024-04-29_21-26-53 | null | [
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"bert",
"feature-extraction",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-29T21:26:53+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #bert #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.
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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": []} | efeno/llama3_RAFT | null | [
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"region:us"
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"1910.09700"
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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unconditional-image-generation | diffusers |
# Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
This model is a diffusion model for unconditional image generation of cute 🦋.
## Usage
```python
from diffusers import DDPMPipeline
pipeline = DDPMPipeline.from_pretrained('Joanton/sd-class-butterflie... | {"license": "mit", "tags": ["pytorch", "diffusers", "unconditional-image-generation", "diffusion-models-class"]} | Joanton/sd-class-butterflies-32 | null | [
"diffusers",
"safetensors",
"pytorch",
"unconditional-image-generation",
"diffusion-models-class",
"license:mit",
"diffusers:DDPMPipeline",
"region:us"
] | null | 2024-04-29T21:28:05+00:00 | [] | [] | TAGS
#diffusers #safetensors #pytorch #unconditional-image-generation #diffusion-models-class #license-mit #diffusers-DDPMPipeline #region-us
|
# Model Card for Unit 1 of the Diffusion Models Class
This model is a diffusion model for unconditional image generation of cute .
## Usage
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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/cavwnn7 | null | [
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# Model Card for Model ID
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sentence-similarity | sentence-transformers | # Venusaur
This is a distill of [Bulbasaur](https://huggingface.co/Mihaiii/Bulbasaur) using [qa-assistant](https://huggingface.co/datasets/Mihaiii/qa-assistant).
## Intended purpose
<span style="color:blue">This model is designed for use in semantic-autocomplete ([click here for demo](https://mihaiii.github.io/seman... | {"license": "mit", "library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "gte", "mteb"], "datasets": ["Mihaiii/qa-assistant"], "base_model": "Mihaiii/Bulbasaur", "pipeline_tag": "sentence-similarity", "model-index": [{"name": "Venusaur", "results": [{"ta... | Mihaiii/Venusaur | null | [
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| # Venusaur
This is a distill of Bulbasaur using qa-assistant.
## Intended purpose
<span style="color:blue">This model is designed for use in semantic-autocomplete (click here for demo).</span>
## Usage (Sentence-Transformers) (same as gte-tiny)
Using this model becomes easy when you have sentence-transformers inst... | [
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null | fastai |
# Amazing!
🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([docume... | {"tags": ["fastai"]} | adperem/entregable2 | null | [
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#fastai #region-us #has_space
|
# Amazing!
Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the documentation here)!
2. Create a demo in Gradio or Streamlit using Spaces (documentation here).
3. Join the fastai community on the ... | [
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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": []} | tennant/llava-llama-3-8b-hqedit | null | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | whizzzzkid/nose_gemma_ft91 | null | [
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null | transformers | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/bigcode/starcoder2-15b-instruct-v0.1
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they ... | {"language": ["en"], "license": "bigcode-openrail-m", "library_name": "transformers", "tags": ["code"], "datasets": ["bigcode/self-oss-instruct-sc2-exec-filter-50k"], "base_model": "bigcode/starcoder2-15b-instruct-v0.1", "quantized_by": "mradermacher"} | mradermacher/starcoder2-15b-instruct-v0.1-GGUF | null | [
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| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | whizzzzkid/nous_sevens71 | null | [
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text-generation | transformers |
# Model Card for Model ID
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## Model Details
### Model Description
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | shallow6414/v32k1no | null | [
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null | peft |
# Model Card for Model ID
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<!-- Provide a longer summary of what this model is. -->
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text-generation | transformers |
# Uploaded model
- **Developed by:** 1024m
- **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/mai... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | 1024m/LLAMA3-SMM4H-Task5-16bit | null | [
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# Uploaded model
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- License: apache-2.0
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K9ac-seqsight_16384_512_34M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](http... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H3K9ac-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_16384_512_34M-L8_f | null | [
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| GUE\_EMP\_H3K9ac-seqsight\_16384\_512\_34M-L8\_f
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
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* Loss: 0.4780
* F1 Score: 0... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K9ac-seqsight_16384_512_34M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_34M](http... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_34M", "model-index": [{"name": "GUE_EMP_H3K9ac-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_16384_512_34M-L1_f | null | [
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| GUE\_EMP\_H3K9ac-seqsight\_16384\_512\_34M-L1\_f
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4837
* F1 Score: 0... | [
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null | transformers |
# Uploaded model
- **Developed by:** bincoder
- **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"} | bincoder/lora_model-PFG | null | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | tennant/llava-llama-3-8b-vanilla | null | [
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# GUE_EMP_H3K9ac-seqsight_16384_512_34M-L32_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_H3K9ac-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_16384_512_34M-L32_f | null | [
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| GUE\_EMP\_H3K9ac-seqsight\_16384\_512\_34M-L32\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4951
* F1 Score:... | [
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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": []} | hugozanini/fine-tunning-tutorial | null | [
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# Model Card for Model ID
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-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. -->
# Sentimiento-appmovilesPG
This model is a fine-tuned version of [pysentimiento/robertuito-sentiment-analysis](https://huggingface... | {"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "pysentimiento/robertuito-sentiment-analysis", "model-index": [{"name": "Sentimiento-appmovilesPG", "results": []}]} | misaza/Sentimiento-appmovilesPG | null | [
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| Sentimiento-appmovilesPG
========================
This model is a fine-tuned version of pysentimiento/robertuito-sentiment-analysis on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3058
* Accuracy: 0.9367
* F1: 0.8364
Model description
-----------------
More information ne... | [
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text-generation | null | # Llama-3-Open-Ko-8B-GGUF
- Original model: [Llama-3-Open-Ko-8B](https://huggingface.co/beomi/Llama-3-Open-Ko-8B)
<!-- description start -->
## Description
This repo contains GGUF format model files for [Llama-3-Open-Ko-8B](https://huggingface.co/beomi/Llama-3-Open-Ko-8B).
<!-- description end -->
<!-- README_GGUF.m... | {"language": ["en", "ko"], "license": "other", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3", "llama-3-ko", "GGUF"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE", "quantized_by": "andrijdavid"} | LiteLLMs/Llama-3-Open-Ko-8B-GGUF | null | [
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| Llama-3-Open-Ko-8B-GGUF
=======================
* Original model: Llama-3-Open-Ko-8B
Description
-----------
This repo contains GGUF format model files for Llama-3-Open-Ko-8B.
### About GGUF
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null | transformers |
# Uploaded model
- **Developed by:** 1024m
- **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/mai... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | 1024m/LLAMA3-SMM4H-Task5-LoRA | null | [
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# Uploaded model
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text-generation | transformers |
# Uploaded model
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null | transformers |
# Uploaded model
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null | transformers |
# Uploaded model
- **Developed by:** tingting
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text-generation | transformers | # merged
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [Azazelle/Llama-3-8B-contaminated-roleplay](https://huggingface.co/... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["Azazelle/Llama-3-8B-contaminated-roleplay", "ResplendentAI/Aura_Uncensored_l3_8B", "Undi95/Llama-3-LewdPlay-8B-evo", "ajibawa-2023/Scarlett-Llama-3-8B", "MaziyarPanahi/Llama-3-8B-Instruct-DPO-v0.3"]} | Azazelle/Llama-3-8B-Help-Me | null | [
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"base_model:ajibawa-2023/... | null | 2024-04-29T21:54:49+00:00 | [
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This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the Model Stock merge method using Azazelle/Llama-3-8B-contaminated-roleplay as a base.
### Models Merged
The following models were included in the merge:
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null | transformers |
# Uploaded model
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[<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_100 | null | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me3-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_H3K4me3-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_16384_512_34M-L8_f | null | [
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| GUE\_EMP\_H3K4me3-seqsight\_16384\_512\_34M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
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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_H3K4me3-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_H3K4me3-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_16384_512_34M-L1_f | null | [
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| GUE\_EMP\_H3K4me3-seqsight\_16384\_512\_34M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
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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": []} | cilantro9246/6hb0u7i | null | [
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# Model Card for Model ID
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me3-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_H3K4me3-seqsight_16384_512_34M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_16384_512_34M-L32_f | null | [
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| GUE\_EMP\_H3K4me3-seqsight\_16384\_512\_34M-L32\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_34M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
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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-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_H4-seqsight_16384_512_34M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4-seqsight_16384_512_34M-L8_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-L8\_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: 0.2635
* F1 Score: 0.8955
* Accu... | [
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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-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_H4-seqsight_16384_512_34M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4-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\_H4-seqsight\_16384\_512\_34M-L1\_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: 0.2515
* F1 Score: 0.9028
* Accu... | [
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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. -->
# emotion-classifier
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "roberta-base", "model-index": [{"name": "emotion-classifier", "results": []}]} | scspinney/emotion-classifier | null | [
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] | null | 2024-04-29T22:00:23+00:00 | [] | [] | TAGS
#transformers #safetensors #roberta #text-classification #generated_from_trainer #base_model-roberta-base #license-mit #autotrain_compatible #endpoints_compatible #region-us
| emotion-classifier
==================
This model is a fine-tuned version of roberta-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2192
* Accuracy: 0.9343
Model description
-----------------
More information needed
Intended uses & limitations
---------------------... | [
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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. -->
# t5-base_te
This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dat... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "base_model": "google-t5/t5-base", "model-index": [{"name": "t5-base_te", "results": []}]} | lesha-grishchenko/t5-base_te | null | [
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| t5-base\_te
===========
This model is a fine-tuned version of google-t5/t5-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 3.3917
* Bleu: 0.0241
* Gen Len: 19.0
Model description
-----------------
More information needed
Intended uses & limitations
----------------... | [
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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. -->
# 0.0001_3iters_bs256_nodpo_full6w_userresponse_iter_2
This model is a fine-tuned version of [ShenaoZhang/0.0001_3iters_bs256_nodp... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "ShenaoZhang/0.0001_3iters_bs256_nodpo_full6w_userresponse_iter_1", "model-index": [{"name": "0.0001_3iters_bs256_nodpo_full6w_userresponse_iter_2", "re... | ShenaoZhang/0.0001_3iters_bs256_nodpo_full6w_userresponse_iter_2 | null | [
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# 0.0001_3iters_bs256_nodpo_full6w_userresponse_iter_2
This model is a fine-tuned version of ShenaoZhang/0.0001_3iters_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... | [
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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": []} | shallow6414/6h8psvj | null | [
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] | null | 2024-04-29T22:04:27+00:00 | [
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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-generation | transformers |
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_pat... | {"license": "other", "library_name": "transformers", "tags": ["autotrain", "text-generation-inference", "text-generation", "peft"], "widget": [{"messages": [{"role": "user", "content": "What is your favorite condiment?"}]}]} | aniketarahane/autotrain-omkul-hydox | null | [
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|
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
# Usage
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null | transformers | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/yzhuang/Meta-Llama-3-8B-Instruct_fictional_arc_German_v2
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at t... | {"language": ["en"], "license": "other", "library_name": "transformers", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "yzhuang/Meta-Llama-3-8B-Instruct_fictional_arc_German_v2", "quantized_by": "mradermacher"} | mradermacher/Meta-Llama-3-8B-Instruct_fictional_arc_German_v2-GGUF | null | [
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] | null | 2024-04-29T22:04:41+00:00 | [] | [
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| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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] |
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_400 | 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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question-answering | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# omarSorour123/sorour_qa_model
This model is a fine-tuned version of [timpal0l/mdeberta-v3-base-squad2](https://huggingface.co/timpal0l... | {"language": ["ar"], "license": "mit", "tags": ["generated_from_keras_callback"], "base_model": "timpal0l/mdeberta-v3-base-squad2", "model-index": [{"name": "omarSorour123/sorour_qa_model", "results": []}]} | gp-tar4/QA_FineTuned_mdeberta-v3-base-squad2 | null | [
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| omarSorour123/sorour\_qa\_model
===============================
This model is a fine-tuned version of timpal0l/mdeberta-v3-base-squad2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.6044
* Validation Loss: 1.6929
* Epoch: 4
Model description
-----------------
Mor... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam', 'weight\\_decay': None, 'clipnorm': None, 'global\\_clipnorm': None, 'clipvalue': None, 'use\\_ema': False, 'ema\\_momentum': 0.99, 'ema\\_overwrite\\_frequency': None, 'jit\\_compile': Tru... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam',... | [
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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_40 | 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"/>
| [
"# Uploaded model\n\n- Developed by: tingting\n- License: apache-2.0\n- Finetuned from model : unsloth/llama-3-8b-bnb-4bit\n\nThis llama model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - embracellm/sushi05_LoRA
<Gallery />
## Model description
These are embracellm/sushi05_LoRA LoR... | {"license": "openrail++", "library_name": "diffusers", "tags": ["text-to-image", "text-to-image", "diffusers-training", "diffusers", "dora", "template:sd-lora", "stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "text-to-image", "diffusers-training", "diffusers", "dora", "template:sd-lora", "stabl... | embracellm/sushi05_LoRA | null | [
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"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"region:us"
] | null | 2024-04-29T22:08:49+00:00 | [] | [] | TAGS
#diffusers #tensorboard #text-to-image #diffusers-training #dora #template-sd-lora #stable-diffusion-xl #stable-diffusion-xl-diffusers #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-openrail++ #region-us
|
# SDXL LoRA DreamBooth - embracellm/sushi05_LoRA
<Gallery />
## Model description
These are embracellm/sushi05_LoRA LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using DreamBooth.
LoRA for the text encoder was enabled: False.
Special VAE used for training: madeb... | [
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"## Model description\n\nThese are embracellm/sushi05_LoRA LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.\n\nThe weights were trained using DreamBooth.\n\nLoRA for the text encoder was enabled: False.\n\nSpecial VAE used for ... | [
"TAGS\n#diffusers #tensorboard #text-to-image #diffusers-training #dora #template-sd-lora #stable-diffusion-xl #stable-diffusion-xl-diffusers #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-openrail++ #region-us \n",
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