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null | transformers |
# reach-vb/llama-3-8b-Q8_0-GGUF
This model was converted to GGUF format from [`unsloth/llama-3-8b`](https://huggingface.co/unsloth/llama-3-8b) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/unsloth/l... | {"language": ["en"], "license": "llama2", "library_name": "transformers", "tags": ["unsloth", "transformers", "llama", "llama-3", "llama-cpp", "gguf-my-repo"]} | reach-vb/llama-3-8b-Q8_0-GGUF | null | [
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|
# reach-vb/llama-3-8b-Q8_0-GGUF
This model was converted to GGUF format from 'unsloth/llama-3-8b' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CLI:
Server:
Note: You can ... | [
"# reach-vb/llama-3-8b-Q8_0-GGUF\nThis model was converted to GGUF format from 'unsloth/llama-3-8b' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
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text-to-image | diffusers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
... | {"library_name": "diffusers"} | Niggendar/genericpony_v20 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mistral-journal-finetune
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mist... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "mistral-journal-finetune", "results": []}]} | dendimaki/mistral-journal-finetune | null | [
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#peft #safetensors #generated_from_trainer #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #region-us
|
# mistral-journal-finetune
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.1399
- eval_runtime: 1839.75
- eval_samples_per_second: 0.231
- eval_steps_per_second: 0.029
- epoch: 0.0294
- step: 50
## Model ... | [
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text-generation | transformers |
# Model Card for Gemma fine-tuned model
Developed by Dattaraj Rao from Persistent by fine-tuning Gemma-2b model on mental health Q&A dataset.
## Model Details: Instruction tuned model foir answering ... | {"license": "apache-2.0", "library_name": "transformers", "tags": ["medical"], "datasets": ["Amod/mental_health_counseling_conversations"]} | dattaraj/Gemma-2b-it-mental-health | null | [
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|
!Persistent
# Model Card for Gemma fine-tuned model
Developed by Dattaraj Rao from Persistent by fine-tuning Gemma-2b model on mental health Q&A dataset.
## Model Details: Instruction tuned model foir answering questions from mental health patients.
### Model Description: Instruction tuned model foir answering qu... | [
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text-generation | transformers | # SQL-Llama-v0.5 | {} | IceKingBing/SQL-Llama-v0.5 | null | [
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"llama",
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#transformers #safetensors #llama #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/NotAiLOL/Knight-Mixtral-WizardLM-140B-MoE
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher... | {"language": ["en"], "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": "NotAiLOL/Knight-Mixtral-WizardLM-140B-MoE", "quantized_by": "mradermacher"} | mradermacher/Knight-Mixtral-WizardLM-140B-MoE-i1-GGUF | null | [
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#transformers #gguf #mergekit #merge #en #base_model-NotAiLOL/Knight-Mixtral-WizardLM-140B-MoE #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. ... | [] | [
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zero-shot-image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# clip-seed-vit-roberta
This model is a fine-tuned version of [openai/clip-vit-base-patch16](https://huggingface.co/openai/clip-vi... | {"tags": ["generated_from_trainer"], "base_model": "openai/clip-vit-base-patch16", "model-index": [{"name": "clip-seed-vit-roberta", "results": []}]} | zabir735/clip-seed-vit-roberta | null | [
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"endpoints_compatible",
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#transformers #safetensors #clip #zero-shot-image-classification #generated_from_trainer #base_model-openai/clip-vit-base-patch16 #endpoints_compatible #region-us
|
# clip-seed-vit-roberta
This model is a fine-tuned version of openai/clip-vit-base-patch16 on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyp... | [
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token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-ar
This model is a fine-tuned version of [tner/xlm-roberta-base-panx-dataset-ar](https://hugging... | {"tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "tner/xlm-roberta-base-panx-dataset-ar", "model-index": [{"name": "xlm-roberta-base-finetuned-panx-ar", "results": []}]} | yousefz25/xlm-roberta-base-finetuned-panx-ar | null | [
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| xlm-roberta-base-finetuned-panx-ar
==================================
This model is a fine-tuned version of tner/xlm-roberta-base-panx-dataset-ar on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1977
* F1: 0.8803
Model description
-----------------
More information neede... | [
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text-generation | transformers | # lobotollama6b
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 passthrough merge method.
### Models Merged
The following models were included in the merge:
* /home/meow/hf/Meta-Llama-3-8B-... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": []} | labotollama3/lobotollama-5.5b | null | [
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"safetensors",
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"text-generation",
"mergekit",
"merge",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
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#transformers #safetensors #llama #text-generation #mergekit #merge #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # lobotollama6b
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the passthrough merge method.
### Models Merged
The following models were included in the merge:
* /home/meow/hf/Meta-Llama-3-8B-Instruct
### Configuration
The foll... | [
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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": []} | Keeynoti/finetuning-wav2vec-large-swahili-asr-model_v10-trial2 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-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": []} | llm-tester125/bertHatespeechTest | null | [
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## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
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token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-ar
This model is a fine-tuned version of [tner/xlm-roberta-base-panx-dataset-ar](https://hugging... | {"tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "tner/xlm-roberta-base-panx-dataset-ar", "model-index": [{"name": "xlm-roberta-base-finetuned-panx-ar", "results": []}]} | JumanaYosri/xlm-roberta-base-finetuned-panx-ar | null | [
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| xlm-roberta-base-finetuned-panx-ar
==================================
This model is a fine-tuned version of tner/xlm-roberta-base-panx-dataset-ar on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1977
* F1: 0.8803
Model description
-----------------
More information neede... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 1",
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n*... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | OwOOwO/dumbo-llama8 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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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. -->
# results_2
This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknow... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "google/flan-t5-small", "model-index": [{"name": "results_2", "results": []}]} | sanjithrj/results_2 | null | [
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| results\_2
==========
This model is a fine-tuned version of google/flan-t5-small on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.6490
* Rouge1: 0.4530
* Rouge2: 0.2185
* Rougel: 0.3802
* Rougelsum: 0.4180
Model description
-----------------
More information needed
Int... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 5",
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null | 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": []} | zandfj/LLaMA2-7B-Chat-lora-nq-tet-robust-042214-nonoresprompt | null | [
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#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- License... | [
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null | null | Glucotanol là gì?
Glucotanol là một loại xi-rô dạng lỏng uống mang tính cách mạng được bào chế để hỗ trợ các cá nhân quản lý bệnh tiểu đường. Không giống như các loại thuốc truyền thống, Glucotanol cung cấp một giải pháp tiện lợi và dễ sử dụng chứa đầy các chất dinh dưỡng thiết yếu. Bổ sung cải tiến này được thiết kế ... | {"license": "apache-2.0"} | GlucotanolVietnam/GlucotanolVietnam | null | [
"license:apache-2.0",
"region:us"
] | null | 2024-04-22T07:27:13+00:00 | [] | [] | TAGS
#license-apache-2.0 #region-us
| Glucotanol là gì?
Glucotanol là một loại xi-rô dạng lỏng uống mang tính cách mạng được bào chế để hỗ trợ các cá nhân quản lý bệnh tiểu đường. Không giống như các loại thuốc truyền thống, Glucotanol cung cấp một giải pháp tiện lợi và dễ sử dụng chứa đầy các chất dinh dưỡng thiết yếu. Bổ sung cải tiến này được thiết kế ... | [] | [
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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": []} | Keeynoti/finetuning-wav2vec-large-swahili-asr-model_v10-kaggle | null | [
"transformers",
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#transformers #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- License... | [
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text-classification | transformers | ## load model
tuned_bert_model = BertForSequenceClassification.from_pretrained('YC9Z/tesla_news_title_sentiment_analysis', id2label={0: 'Neutral', 1: 'Positive', 2: 'Negative'})
senti_tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
## example:
inputs = senti_tokenizer("I like you. I love you", padding=... | {} | YC9Z/tesla_news_title_sentiment_analysis | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-22T07:31:12+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us
| ## load model
tuned_bert_model = BertForSequenceClassification.from_pretrained('YC9Z/tesla_news_title_sentiment_analysis', id2label={0: 'Neutral', 1: 'Positive', 2: 'Negative'})
senti_tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
## example:
inputs = senti_tokenizer("I like you. I love you", padding=... | [
"## load model\ntuned_bert_model = BertForSequenceClassification.from_pretrained('YC9Z/tesla_news_title_sentiment_analysis', id2label={0: 'Neutral', 1: 'Positive', 2: 'Negative'})\n\nsenti_tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')",
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text-generation | null |
# cleatherbury/Calme-7B-Instruct-v0.9-Q8_0-GGUF
This model was converted to GGUF format from [`MaziyarPanahi/Calme-7B-Instruct-v0.9`](https://huggingface.co/MaziyarPanahi/Calme-7B-Instruct-v0.9) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [o... | {"license": "apache-2.0", "tags": ["generated_from_trainer", "mistral", "7b", "calme", "llama-cpp", "gguf-my-repo"], "inference": false, "model_creator": "MaziyarPanahi", "pipeline_tag": "text-generation", "quantized_by": "MaziyarPanahi", "model-index": [{"name": "Calme-7B-Instruct-v0.9", "results": []}]} | cleatherbury/Calme-7B-Instruct-v0.9-Q8_0-GGUF | null | [
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"mistral",
"7b",
"calme",
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"gguf-my-repo",
"text-generation",
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"region:us"
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#gguf #generated_from_trainer #mistral #7b #calme #llama-cpp #gguf-my-repo #text-generation #license-apache-2.0 #region-us
|
# cleatherbury/Calme-7B-Instruct-v0.9-Q8_0-GGUF
This model was converted to GGUF format from 'MaziyarPanahi/Calme-7B-Instruct-v0.9' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
... | [
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text-to-image | diffusers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
... | {"library_name": "diffusers"} | Niggendar/aaaautismPonyFinetune_prototypeV2 | null | [
"diffusers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
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#diffusers #safetensors #arxiv-1910.09700 #endpoints_compatible #diffusers-StableDiffusionXLPipeline #region-us
|
# Model Card for Model ID
## Model Details
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This is the model card of a diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# 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": []} | nilz1999/Llama-2-7b-FT-text-segmentation-ft-merged | null | [
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"text-generation",
"arxiv:1910.09700",
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
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- License... | [
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 0.0_ablation_5iters_iter_5
This model is a fine-tuned version of [ZhangShenao/0.0_ablation_5iters_iter_4](https://huggingface.co... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["ZhangShenao/0.0_ablation_5iters_dataset"], "base_model": "ZhangShenao/0.0_ablation_5iters_iter_4", "model-index": [{"name": "0.0_ablation_5iters_iter_5", "results": []}]} | ZhangShenao/0.0_ablation_5iters_iter_5 | null | [
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"endpo... | null | 2024-04-22T07:38:21+00:00 | [] | [] | TAGS
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# 0.0_ablation_5iters_iter_5
This model is a fine-tuned version of ZhangShenao/0.0_ablation_5iters_iter_4 on the ZhangShenao/0.0_ablation_5iters_dataset dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information... | [
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audio-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_awesome_mind_model
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-ba... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["minds14"], "metrics": ["accuracy"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "my_awesome_mind_model", "results": [{"task": {"type": "audio-classification", "name": "Audio Classification"}, "dataset": {"name": "minds14", ... | syedmohiuddinzia/my_awesome_mind_model | null | [
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| my\_awesome\_mind\_model
========================
This model is a fine-tuned version of facebook/wav2vec2-base on the minds14 dataset.
It achieves the following results on the evaluation set:
* Loss: 2.6442
* Accuracy: 0.0354
Model description
-----------------
More information needed
Intended uses & limitati... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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text2text-generation | 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. -->
# englishtohinditranslator
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-hi](https://huggingface.co/Helsinki-NLP/opus-m... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "Helsinki-NLP/opus-mt-en-hi", "model-index": [{"name": "englishtohinditranslator", "results": []}]} | upendrawappgo/englishtohinditranslator | null | [
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| englishtohinditranslator
========================
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-hi on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 3.7671
* Validation Loss: 3.9485
* Epoch: 0
Model description
-----------------
More information needed... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | ohsuz/ohsuz-fin-warm-start-e1 | 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": []} | nilz1999/Llama-2-7b-FT-single-label-ft-merged | null | [
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null | transformers |
# Uploaded model
- **Developed by:** xkiwilabs
- **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"} | xkiwilabs/lora_opLLama3_modelv4 | null | [
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|
# Uploaded model
- Developed by: xkiwilabs
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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text-generation | transformers | # ResplendentAI/Aurora_l3_8B AWQ
- Model creator: [ResplendentAI](https://huggingface.co/ResplendentAI)
- Original model: [Aurora_l3_8B](https://huggingface.co/ResplendentAI/Aurora_l3_8B)
## How to use
### Install the necessary packages
```bash
pip install --upgrade autoawq autoawq-kernels
```
### Example Python... | {"library_name": "transformers", "tags": ["4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/Aurora_l3_8B-AWQ | null | [
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#transformers #safetensors #llama #text-generation #4-bit #AWQ #autotrain_compatible #endpoints_compatible #conversational #text-generation-inference #region-us
| # ResplendentAI/Aurora_l3_8B AWQ
- Model creator: ResplendentAI
- Original model: Aurora_l3_8B
## How to use
### Install the necessary packages
### Example Python code
### About AWQ
AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Co... | [
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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": []} | nilz1999/Llama-2-7b-FT-multi-label-ft-merged | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/ludis/tsukasa-llama-3-8b-qlora
<!-- 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", "datasets": ["PygmalionAI/PIPPA", "lemonilia/LimaRP"], "base_model": "ludis/tsukasa-llama-3-8b-qlora", "quantized_by": "mradermacher"} | mradermacher/tsukasa-llama-3-8b-qlora-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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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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image-classification | transformers |
# Model Card for Ad Recognition Model
## Model Details
### Model Description
- **Developed by:** Kamesh Rsk (KameshRsk)
- **Model type:** Vision Transformer (ViT) for image classification
- **Language(s) (NLP):** N/A
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- **Finetuned from model:** google/vit-base-patch16-224
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- Model type: Vision Transformer (ViT) for image classification
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text-generation | transformers | # lobotollama6.5b 26/32 layer prune
This model was merged using the passthrough merge method.
### Models Merged
The following models were included in the merge:
* /home/meow/hf/Meta-Llama-3-8B-Instruct
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| # lobotollama6.5b 26/32 layer prune
This model was merged using the passthrough merge method.
### Models Merged
The following models were included in the merge:
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image-text-to-text | xtuner |
<div align="center">
<img src="https://github.com/InternLM/lmdeploy/assets/36994684/0cf8d00f-e86b-40ba-9b54-dc8f1bc6c8d8" width="600"/>
[](https://github.com/InternLM/xtuner)
</div>
## Model
llava-llama-3-8b is a LLaVA model fine-tuned fr... | {"library_name": "xtuner", "datasets": ["liuhaotian/LLaVA-Pretrain", "liuhaotian/LLaVA-Instruct-150K"], "pipeline_tag": "image-text-to-text"} | xtuner/llava-llama-3-8b | null | [
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![Generic badge](URL
Model
-----
llava-llama-3-8b is a LLaVA model fine-tuned from meta-llama/Meta-Llama-3-8B-Instruct and CLIP-ViT-Large-patch14-336 with LLaVA-Pretrain and LLaVA-Instruct by XTuner.
Note: This model is in XTuner LLaVA format.
Resources:
* GitHub: xtuner
* HuggingFace LLaVA ... | [
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text-generation | transformers | # flammenai/flammen20-mistral-7B AWQ
- Model creator: [flammenai](https://huggingface.co/flammenai)
- Original model: [flammen20-mistral-7B](https://huggingface.co/flammenai/flammen20-mistral-7B)
## How to use
### Install the necessary packages
```bash
pip install --upgrade autoawq autoawq-kernels
```
### Exampl... | {"library_name": "transformers", "tags": ["4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/flammen20-mistral-7B-AWQ | null | [
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- Model creator: flammenai
- Original model: flammen20-mistral-7B
## How to use
### Install the necessary packages
### Example Python code
### About AWQ
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 0.0_ablation_6iters_iter_6
This model is a fine-tuned version of [ZhangShenao/0.0_ablation_6iters_iter_5](https://huggingface.co... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["ZhangShenao/0.0_ablation_6iters_dataset"], "base_model": "ZhangShenao/0.0_ablation_6iters_iter_5", "model-index": [{"name": "0.0_ablation_6iters_iter_6", "results": []}]} | ZhangShenao/0.0_ablation_6iters_iter_6 | null | [
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# 0.0_ablation_6iters_iter_6
This model is a fine-tuned version of ZhangShenao/0.0_ablation_6iters_iter_5 on the ZhangShenao/0.0_ablation_6iters_dataset dataset.
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More information needed
## Intended uses & limitations
More information needed
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
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<!-- Provide a longer summary of what this model is. -->
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- **Funded by [optional]:** [More Information Needed]
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mbart-traduct
This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on... | {"license": "mit", "tags": ["simplification", "generated_from_trainer"], "metrics": ["bleu"], "base_model": "facebook/mbart-large-50", "model-index": [{"name": "mbart-traduct", "results": []}]} | lauragordo/mbart-traduct | null | [
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| mbart-traduct
=============
This model is a fine-tuned version of facebook/mbart-large-50 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4130
* Bleu: 28.0367
* Gen Len: 19.933
Model description
-----------------
More information needed
Intended uses & limitations
---... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/crestf411/llama-3-daybreak-v0.1-8b-hf
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they d... | {"language": ["en"], "library_name": "transformers", "tags": ["not-for-all-audiences"], "base_model": "crestf411/llama-3-daybreak-v0.1-8b-hf", "quantized_by": "mradermacher"} | mradermacher/llama-3-daybreak-v0.1-8b-hf-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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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/MaziyarPanahi/Llama-3-11B
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show u... | {"language": ["en"], "license": "other", "library_name": "transformers", "tags": ["mergekit", "merge", "facebook", "meta", "pytorch", "llama", "llama-3"], "model_name": "Llama-3-11B", "base_model": "MaziyarPanahi/Llama-3-11B", "license_link": "LICENSE", "license_name": "llama3", "model_creator": "MaziyarPanahi", "quant... | mradermacher/Llama-3-11B-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 | # nbeerbower/llama-3-bophades-v1-8B AWQ
- Model creator: [nbeerbower](https://huggingface.co/nbeerbower)
- Original model: [llama-3-bophades-v1-8B](https://huggingface.co/nbeerbower/llama-3-bophades-v1-8B)
## How to use
### Install the necessary packages
```bash
pip install --upgrade autoawq autoawq-kernels
```
... | {"library_name": "transformers", "tags": ["4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/llama-3-bophades-v1-8B-AWQ | null | [
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| # nbeerbower/llama-3-bophades-v1-8B AWQ
- Model creator: nbeerbower
- Original model: llama-3-bophades-v1-8B
## How to use
### Install the necessary packages
### Example Python code
### About AWQ
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text-generation | transformers |
# Swahili llama 3 8b
- **Developed by:** GodsonNtungi
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
An experimental model with poor performing results, but a great start
**training run** : 1 epoch \
**time**: 9 hours : 20 mins : 07 seconds\
**training loss**: 0.8683
**PEFT para... | {"language": ["sw"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl", "sft"], "datasets": "mwitiderrick/SwahiliAlpaca", "base_model": "llama-3-8b", "pipeline_tag": "text-generation"} | GodsonNtungi/swahilillama3-8b | null | [
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|
# Swahili llama 3 8b
- Developed by: GodsonNtungi
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
An experimental model with poor performing results, but a great start
training run : 1 epoch \
time: 9 hours : 20 mins : 07 seconds\
training loss: 0.8683
PEFT parameters
Weakness \
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fill-mask | 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. -->
# e5-small-wb-descriptions
This model is a fine-tuned version of [intfloat/multilingual-e5-small](https://huggingface.co/intfloat/... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "intfloat/multilingual-e5-small", "model-index": [{"name": "e5-small-wb-descriptions", "results": []}]} | vkimbris/e5-small-wb-descriptions | null | [
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|
# e5-small-wb-descriptions
This model is a fine-tuned version of intfloat/multilingual-e5-small on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Trainin... | [
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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": []} | Ratna1704/vit-base-patch16-224-in21k-finetuned-lora-food101 | null | [
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# flant-t5-small-function-calling
This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "google/flan-t5-small", "model-index": [{"name": "flant-t5-small-function-calling", "results": []}]} | jrcastropy/flan-t5-small-query-extraction | null | [
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| flant-t5-small-function-calling
===============================
This model is a fine-tuned version of google/flan-t5-small on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0000
* Rouge1: 58.4404
* Rouge2: 51.6574
* Rougel: 58.4415
* Rougelsum: 58.4417
* Gen Len: 19.0
Model d... | [
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null | transformers |
# Uploaded model
- **Developed by:** kpi
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-2b-bnb-4bit
This gemma model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/im... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "gemma", "trl"], "base_model": "unsloth/gemma-2b-bnb-4bit"} | kpi/news-extract-paritial-516 | null | [
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# Uploaded model
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- License: apache-2.0
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<img src="URL width="200"/>
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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": []} | pphuc25/bge-m3-unsupervised-split-digit | null | [
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## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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## 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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image-text-to-text | xtuner |
<div align="center">
<img src="https://github.com/InternLM/lmdeploy/assets/36994684/0cf8d00f-e86b-40ba-9b54-dc8f1bc6c8d8" width="600"/>
[](https://github.com/InternLM/xtuner)
</div>
## Model
llava-llama-3-8b-v1_1 is a LLaVA model fine-tun... | {"library_name": "xtuner", "datasets": ["Lin-Chen/ShareGPT4V"], "pipeline_tag": "image-text-to-text"} | xtuner/llava-llama-3-8b-v1_1 | null | [
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|
![Generic badge](URL
Model
-----
llava-llama-3-8b-v1\_1 is a LLaVA model fine-tuned from meta-llama/Meta-Llama-3-8B-Instruct and CLIP-ViT-Large-patch14-336 with ShareGPT4V-PT and InternVL-SFT by XTuner.
Note: This model is in XTuner LLaVA format.
Resources:
* GitHub: xtuner
* HuggingFace LLa... | [
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null | null | # BigTranslate: Augmenting Large Language Models with Multilingual Translation Capability over 100 Languages
Large language models (LLMs) demonstrate promising translation performance among various natural languages. However, many LLMs especially the open-sourced ones, such as BLOOM and LLaMA, are English-dominant and ... | {"license": "lgpl-3.0"} | AliciaTestarossa/BigTranslate-13b-GGUF | null | [
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| # BigTranslate: Augmenting Large Language Models with Multilingual Translation Capability over 100 Languages
Large language models (LLMs) demonstrate promising translation performance among various natural languages. However, many LLMs especially the open-sourced ones, such as BLOOM and LLaMA, are English-dominant and ... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | nmdr/llama-2-7b-chat-physics-1k-Baymax20 | null | [
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text-generation | transformers | # flammenai/flammen21-mistral-7B AWQ
- Model creator: [flammenai](https://huggingface.co/flammenai)
- Original model: [flammen21-mistral-7B](https://huggingface.co/flammenai/flammen21-mistral-7B)
# Model Summary
A Mist... | {"library_name": "transformers", "tags": ["4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/flammen21-mistral-7B-AWQ | null | [
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| # flammenai/flammen21-mistral-7B AWQ
- Model creator: flammenai
- Original model: flammen21-mistral-7B
!image/png
# Model Summary
A Mistral 7B LLM built from merging pretrained models and finetuning on flammenai/Date-DPO-v2.
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visual-question-answering | 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": []} | GCMcM2024/blip2-opt-2.7b-spanish-without-lora | null | [
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null | transformers |
# Model Card for Model ID
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## 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": []} | MLP-Lemma/Lemma-pt-6000step | null | [
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null | null |
# MindBridge
## Introduction
This repo holds the pretrained weights for MindBridge (https://github.com/littlepure2333/MindBridge)
## Usage
1. Clone the code repo. `git clone https://github.com/littlepure2333/MindBridge.git`
2. Create a directory under the code repo `./train_logs`
3. Download the folder that contain... | {"language": ["en"], "license": "cc-by-nc-sa-4.0"} | littlepure2333/MindBridge | null | [
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# MindBridge
## Introduction
This repo holds the pretrained weights for MindBridge (URL
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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": []} | RefalMachine/ruadapt_llama3_part1-2_vo_1e4 | 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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visual-question-answering | transformers |
<div align="center">
<img src="https://github.com/InternLM/lmdeploy/assets/36994684/0cf8d00f-e86b-40ba-9b54-dc8f1bc6c8d8" width="600"/>
[](https://github.com/InternLM/xtuner)
</div>
## Model
llava-llama-3-8b-v1_1-pretrain is a LLaVA proje... | {"datasets": ["Lin-Chen/ShareGPT4V"], "pipeline_tag": "visual-question-answering"} | xtuner/llava-llama-3-8b-v1_1-pretrain | null | [
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|
<div align="center">
<img src="URL width="600"/>
![Generic badge](URL
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## Model
llava-llama-3-8b-v1_1-pretrain is a LLaVA projector pretrained from Meta-Llama-3-8B-Instruct and CLIP-ViT-Large-patch14-336 on ShareGPT4V-PT dataset by XTuner.
The fine-tuned LLaVA model can be found on xtuner/llava-llama-3-... | [
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"TAGS\n#transformers #visual-question-answering #dataset-Lin-Chen/ShareGPT4V #endpoints_compatible #region-us \n## Model\n\nllava-llama-3-8b-v1_1-pretrain is a LLaVA projector pretrained from Meta-Llama-3-8B-Instruct and CLIP-ViT-Large-patch14-336 on ShareGPT4V-PT dataset by XTuner.\n\nThe fine-tuned LLaVA model ca... |
visual-question-answering | transformers |
<div align="center">
<img src="https://github.com/InternLM/lmdeploy/assets/36994684/0cf8d00f-e86b-40ba-9b54-dc8f1bc6c8d8" width="600"/>
[](https://github.com/InternLM/xtuner)
</div>
## Model
llava-llama-3-8b-pretrain is a LLaVA projector ... | {"datasets": ["liuhaotian/LLaVA-Pretrain"], "pipeline_tag": "visual-question-answering"} | xtuner/llava-llama-3-8b-pretrain | null | [
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"visual-question-answering",
"dataset:liuhaotian/LLaVA-Pretrain",
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#transformers #visual-question-answering #dataset-liuhaotian/LLaVA-Pretrain #endpoints_compatible #region-us
|
<div align="center">
<img src="URL width="600"/>
![Generic badge](URL
</div>
## Model
llava-llama-3-8b-pretrain is a LLaVA projector pretrained from Meta-Llama-3-8B-Instruct and CLIP-ViT-Large-patch14-336 on LLaVA-Pretrain dataset by XTuner.
The fine-tuned LLaVA model can be found on xtuner/llava-llama-3-8b.
... | [
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text-generation | transformers | # What is this?
- MoE model of 2 Llama-3 models:
- vicgalle/Roleplay-Llama-3-8B
- Sao10K/L3-Solana-8B-v1
**Just some experiment, nothing else. I think it not too good for roleplay, you should try it** | {"license": "cc-by-nc-4.0", "tags": ["Roleplay", "roleplay", "moe", "merge"], "base_model": ["vicgalle/Roleplay-Llama-3-8B", "Sao10K/L3-Solana-8B-v1"]} | Alsebay/Kilo-2x8B | null | [
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| # What is this?
- MoE model of 2 Llama-3 models:
- vicgalle/Roleplay-Llama-3-8B
- Sao10K/L3-Solana-8B-v1
Just some experiment, nothing else. I think it not too good for roleplay, you should try it | [
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video-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# videomae-base-finetuned-ucf101-subset
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-N... | {"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "base_model": "MCG-NJU/videomae-base", "model-index": [{"name": "videomae-base-finetuned-ucf101-subset", "results": []}]} | devd-99/videomae-base-finetuned-ucf101-subset | null | [
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"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-22T08:38:57+00:00 | [] | [] | TAGS
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|
# videomae-base-finetuned-ucf101-subset
This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Tra... | [
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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": []} | dzungPaduahsgs/Vistral7B_mix_v1_adafactor_model_8bit_batch_64_lr_4e-5_merged | null | [
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|
# Model Card for Model ID
## Model Details
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers | Mistral-7B German [LAPT + CLP+ (Untied)]
===
## How to use
```python
from peft import AutoPeftModelForCausalLM
from transformers import AutoTokenizer
model = AutoPeftModelForCausalLM.from_pretrained(
"atsuki-yamaguchi/Mistral-7B-v0.1-clpp-untied-de"
)
tokenizer = AutoTokenizer.from_pretrained(
"atsuki-yamaguc... | {"language": "de", "license": "mit"} | atsuki-yamaguchi/Mistral-7B-v0.1-clpp-untied-de | null | [
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"region:us"
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| Mistral-7B German [LAPT + CLP+ (Untied)]
===
## How to use
## Link
For more details, please visit URL
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] |
null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# phi-2-gpo-renew2-b0.001-extra-i1
This model is a fine-tuned version of [DUAL-GPO/phi-2-gpo-renew2-b0.001-i0](https://huggingface... | {"license": "mit", "library_name": "peft", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "microsoft/phi-2", "model-index": [{"name": "phi-2-gpo-renew2-b0.001-extra-i1", "results": []}]} | DUAL-GPO/phi-2-gpo-renew2-b0.001-extra-i1 | null | [
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| phi-2-gpo-renew2-b0.001-extra-i1
================================
This model is a fine-tuned version of DUAL-GPO/phi-2-gpo-renew2-b0.001-i0 on the HuggingFaceH4/ultrafeedback\_binarized dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0421
* Rewards/chosen: -0.0100
* Rewards/rejected: -0.... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-06\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 4\n* seed: 42\n* distributed\\_type: multi-GPU\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam wit... | [
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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. -->
# experiments
This model is a fine-tuned version of [vilm/vinallama-7b-chat](https://huggingface.co/vilm/vinallama-7b-chat) on the... | {"license": "llama2", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "vilm/vinallama-7b-chat", "model-index": [{"name": "experiments", "results": []}]} | trungtienluong/experiments | null | [
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|
# experiments
This model is a fine-tuned version of vilm/vinallama-7b-chat on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The ... | [
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text-generation | transformers | # macadeliccc/Orpo-GutenLlama-3-8B AWQ
- Model creator: [macadeliccc](https://huggingface.co/macadeliccc)
- Original model: [Orpo-GutenLlama-3-8B](https://huggingface.co/macadeliccc/Orpo-GutenLlama-3-8B)
## How to use
### Install the necessary packages
```bash
pip install --upgrade autoawq autoawq-kernels
```
##... | {"library_name": "transformers", "tags": ["4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/Orpo-GutenLlama-3-8B-AWQ | null | [
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"text-generation",
"4-bit",
"AWQ",
"autotrain_compatible",
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"region:us"
] | null | 2024-04-22T08:42:55+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #4-bit #AWQ #autotrain_compatible #endpoints_compatible #conversational #text-generation-inference #region-us
| # macadeliccc/Orpo-GutenLlama-3-8B AWQ
- Model creator: macadeliccc
- Original model: Orpo-GutenLlama-3-8B
## How to use
### Install the necessary packages
### Example Python code
### About AWQ
AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quan... | [
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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": []} | catastropiyush/moondream_finetune_example | 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 | transformers |
# Uploaded model
- **Developed by:** shubham11
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-instruct-v0.2-bnb-4bit
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/u... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-instruct-v0.2-bnb-4bit"} | shubham11/mistralrelease1 | null | [
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# Uploaded model
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- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-instruct-v0.2-bnb-4bit
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<img src="URL width="200"/>
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | nmdr/Mistral-7B-Instruct-v0.2-physics-1k-woody | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | 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": []} | ik28/mistral-med-instruct | null | [
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# Model Card for Model ID
## Model Details
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text-generation | transformers | Based on Meta-Llama-3-8b-Instruct, and is governed by Meta Llama 3 License agreement:
https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct
We don't know how good this model is exactly in benchmarks since we have not benched this yet, but we think real prompts and usage is more telling anyways.
From our testi... | {"license": "apache-2.0"} | AwanLLM/Meta-Llama-3-8B-Instruct-Dolfin-v0.1-exl2-h8-4bpw-exl2 | null | [
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| Based on Meta-Llama-3-8b-Instruct, and is governed by Meta Llama 3 License agreement:
URL
We don't know how good this model is exactly in benchmarks since we have not benched this yet, but we think real prompts and usage is more telling anyways.
From our testing this model is:
- Less Refusals
- More Uncensored
- ... | [] | [
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text-generation | transformers | Mistral-7B Japanese [LAPT + CLP+ (Untied)]
===
## How to use
```python
from peft import AutoPeftModelForCausalLM
from transformers import AutoTokenizer
model = AutoPeftModelForCausalLM.from_pretrained(
"atsuki-yamaguchi/Mistral-7B-v0.1-clpp-untied-ja"
)
tokenizer = AutoTokenizer.from_pretrained(
"atsuki-yamag... | {"language": "ja", "license": "mit"} | atsuki-yamaguchi/Mistral-7B-v0.1-clpp-untied-ja | null | [
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"region:us"
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| Mistral-7B Japanese [LAPT + CLP+ (Untied)]
===
## How to use
## Link
For more details, please visit URL
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] |
image-classification | timm | # Model card for swin_s3_base_224-Foods-101
## Model Details
**Model Name:** Swin Transformer (swin_s3_base_224)
**Architecture:** Swin Transformer
**Pre-trained Model:** Swin Transformer Base (swin_base_patch4_window7_224)
**Fine-tuning Dataset:** Food-101
## Model Description
This model is a fine-tuned version... | {"license": "apache-2.0", "library_name": "timm", "tags": ["image-classification", "timm"], "datasets": ["food101"], "metrics": ["accuracy"]} | OmAlve/swin_s3_base_224-Foods-101 | null | [
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#timm #pytorch #image-classification #dataset-food101 #license-apache-2.0 #region-us
| # Model card for swin_s3_base_224-Foods-101
## Model Details
Model Name: Swin Transformer (swin_s3_base_224)
Architecture: Swin Transformer
Pre-trained Model: Swin Transformer Base (swin_base_patch4_window7_224)
Fine-tuning Dataset: Food-101
## Model Description
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sentence-similarity | sentence-transformers |
# 0xSH1V4M/distilroberta-base-sentence-transformer-triplets
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Trans... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "datasets": ["embedding-data/QQP_triplets"], "pipeline_tag": "sentence-similarity"} | 0xSH1V4M/distilroberta-base-sentence-transformer-triplets | null | [
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|
# 0xSH1V4M/distilroberta-base-sentence-transformer-triplets
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 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 sente... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# phi-2-gpo-renew2-b0.001-log-i0
This model is a fine-tuned version of [lole25/phi-2-sft-lora-ultrachat](https://huggingface.co/lo... | {"license": "mit", "library_name": "peft", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "microsoft/phi-2", "model-index": [{"name": "phi-2-gpo-renew2-b0.001-log-i0", "results": []}]} | DUAL-GPO/phi-2-gpo-renew2-b0.001-log-i0 | null | [
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| phi-2-gpo-renew2-b0.001-log-i0
==============================
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* Rewards/chosen: -0.0859
* Rewards/rejected: -0.1297
* R... | [
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reinforcement-learning | ml-agents |
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
... | {"library_name": "ml-agents", "tags": ["Huggy", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Huggy"]} | Devistra06/ppo-Huggy | null | [
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|
# ppo Agent playing Huggy
This is a trained model of a ppo agent playing Huggy
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/allknowingroger/Llama3merge6-15B-MoE
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["moe", "frankenmoe", "merge", "mergekit", "lazymergekit", "Kukedlc/NeuralLlamita-3-8B-v0.2", "imone/Llama-3-8B-fixed-special-embedding"], "base_model": "allknowingroger/Llama3merge6-15B-MoE", "quantized_by": "mradermacher"} | mradermacher/Llama3merge6-15B-MoE-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": []} | OwOOwO/dumbo-stable_t2 | null | [
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"text-generation",
"conversational",
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# Model Card for Model ID
## Model Details
### Model Description
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token-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": []} | Resi/layoutlmv3-colab | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
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text-generation | transformers | Mistral-7B Swahili [LAPT + CLP+ (Untied)]
===
## How to use
```python
from peft import AutoPeftModelForCausalLM
from transformers import AutoTokenizer
model = AutoPeftModelForCausalLM.from_pretrained(
"atsuki-yamaguchi/Mistral-7B-v0.1-clpp-untied-sw"
)
tokenizer = AutoTokenizer.from_pretrained(
"atsuki-yamagu... | {"language": "sw", "license": "mit"} | atsuki-yamaguchi/Mistral-7B-v0.1-clpp-untied-sw | null | [
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| Mistral-7B Swahili [LAPT + CLP+ (Untied)]
===
## How to use
## Link
For more details, please visit URL
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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... | {"language": ["en"], "library_name": "transformers", "datasets": ["AbhishekG13/BNF_QNA"]} | AbhishekG13/gemma-bnf-qna | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# Llama3merge7-15B-MoE
Llama3merge7-15B-MoE is a Mixture of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Kukedlc/NeuralLlamita-3-8B-v0.2](https://huggingface.co/Kukedlc/NeuralLlamita-3-8B-v0.2)
* [cognitive... | {"license": "apache-2.0", "tags": ["moe", "frankenmoe", "merge", "mergekit", "lazymergekit", "Kukedlc/NeuralLlamita-3-8B-v0.2", "cognitivecomputations/dolphin-2.9-llama3-8b"], "base_model": ["Kukedlc/NeuralLlamita-3-8B-v0.2", "cognitivecomputations/dolphin-2.9-llama3-8b"]} | allknowingroger/Llama3merge7-15B-MoE | null | [
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"base_model:cognitivecomp... | null | 2024-04-22T08:54:50+00:00 | [] | [] | TAGS
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# Llama3merge7-15B-MoE
Llama3merge7-15B-MoE is a Mixture of Experts (MoE) made with the following models using LazyMergekit:
* Kukedlc/NeuralLlamita-3-8B-v0.2
* cognitivecomputations/dolphin-2.9-llama3-8b
## Configuration
## Usage
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feature-extraction | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | stvhuang/rcr-run-5pqr6lwp-90396-master-0_20240402T105012-ep28 | null | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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text-to-image | diffusers |
# Kandinsky 2.2
Kandinsky inherits best practices from Dall-E 2 and Latent diffusion while introducing some new ideas.
It uses the CLIP model as a text and image encoder, and diffusion image prior (mapping) between latent spaces of CLIP modalities. This approach increases the visual performance of the model and unv... | {"license": "apache-2.0", "tags": ["text-to-image", "kandinsky"], "prior": ["kandinsky-community/kandinsky-2-2-prior"], "inference": false} | Shaleen123/kandinsky-2.2-test | null | [
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| Kandinsky 2.2
=============
Kandinsky inherits best practices from Dall-E 2 and Latent diffusion while introducing some new ideas.
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text-generation | transformers | # macadeliccc/Orpo-GutenLlama-3-8B-v2 AWQ
- Model creator: [macadeliccc](https://huggingface.co/macadeliccc)
- Original model: [Orpo-GutenLlama-3-8B-v2](https://huggingface.co/macadeliccc/Orpo-GutenLlama-3-8B-v2)
## How to use
### Install the necessary packages
```bash
pip install --upgrade autoawq autoawq-kernel... | {"library_name": "transformers", "tags": ["4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/Orpo-GutenLlama-3-8B-v2-AWQ | null | [
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| # macadeliccc/Orpo-GutenLlama-3-8B-v2 AWQ
- Model creator: macadeliccc
- Original model: Orpo-GutenLlama-3-8B-v2
## How to use
### Install the necessary packages
### Example Python code
### About AWQ
AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bi... | [
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null | transformers |
# Uploaded model
- **Developed by:** shubham11
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-instruct-v0.2-bnb-4bit
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/u... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-instruct-v0.2-bnb-4bit"} | shubham11/mistralrelease100 | null | [
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# Uploaded model
- Developed by: shubham11
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-instruct-v0.2-bnb-4bit
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<img src="URL width="200"/>
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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. -->
# Llama-450M
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following re... | {"tags": ["generated_from_trainer"], "model-index": [{"name": "Llama-450M", "results": []}]} | ninagroot/Llama-450M | null | [
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| Llama-450M
==========
This model is a fine-tuned version of [](URL on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 5.8986
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Trai... | [
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text-generation | transformers | Based on Meta-Llama-3-8b-Instruct, and is governed by Meta Llama 3 License agreement:
https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct
We don't know how good this model is exactly in benchmarks since we have not benched this yet, but we think real prompts and usage is more telling anyways.
From our testi... | {"license": "apache-2.0"} | AwanLLM/Meta-Llama-3-8B-Instruct-Dolfin-v0.1-exl2-h8-8bpw-exl2 | null | [
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| Based on Meta-Llama-3-8b-Instruct, and is governed by Meta Llama 3 License agreement:
URL
We don't know how good this model is exactly in benchmarks since we have not benched this yet, but we think real prompts and usage is more telling anyways.
From our testing this model is:
- Less Refusals
- More Uncensored
- ... | [] | [
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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. -->
# lenate_model_11_distilbert_trained
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingfac... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "distilbert/distilbert-base-uncased", "model-index": [{"name": "lenate_model_11_distilbert_trained", "results": []}]} | lenate/lenate_model_11_distilbert_trained | null | [
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"license:apache-2.0",
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| lenate\_model\_11\_distilbert\_trained
======================================
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5964
* Accuracy: 0.7332
Model description
-----------------
More inform... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 10",
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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('xhxiao/sd-class-butterflies... | {"license": "mit", "tags": ["pytorch", "diffusers", "unconditional-image-generation", "diffusion-models-class"]} | xhxiao/sd-class-butterflies-32 | null | [
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#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 | # nbeerbower/llama-3-slerp-dolphin-sauce-8B AWQ
- Model creator: [nbeerbower](https://huggingface.co/nbeerbower)
- Original model: [llama-3-slerp-dolphin-sauce-8B](https://huggingface.co/nbeerbower/llama-3-slerp-dolphin-sauce-8B)
## How to use
### Install the necessary packages
```bash
pip install --upgrade autoa... | {"library_name": "transformers", "tags": ["4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/llama-3-slerp-dolphin-sauce-8B-AWQ | null | [
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"text-generation",
"4-bit",
"AWQ",
"autotrain_compatible",
"endpoints_compatible",
"conversational",
"text-generation-inference",
"region:us"
] | null | 2024-04-22T09:04:43+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #4-bit #AWQ #autotrain_compatible #endpoints_compatible #conversational #text-generation-inference #region-us
| # nbeerbower/llama-3-slerp-dolphin-sauce-8B AWQ
- Model creator: nbeerbower
- Original model: llama-3-slerp-dolphin-sauce-8B
## How to use
### Install the necessary packages
### Example Python code
### About AWQ
AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently sup... | [
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reinforcement-learning | sample-factory |
A(n) **APPO** model trained on the **doom_health_gathering_supreme** environment.
This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory.
Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/
## Downloading the model
After installing Sa... | {"library_name": "sample-factory", "tags": ["deep-reinforcement-learning", "reinforcement-learning", "sample-factory"], "model-index": [{"name": "APPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "doom_health_gathering_supreme", "type": "doom_health_ga... | hwting/rl_course_vizdoom_health_gathering_supreme | null | [
"sample-factory",
"tensorboard",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
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#sample-factory #tensorboard #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
A(n) APPO model trained on the doom_health_gathering_supreme environment.
This model was trained using Sample-Factory 2.0: URL
Documentation for how to use Sample-Factory can be found at URL
## Downloading the model
After installing Sample-Factory, download the model with:
## Using the model
To run the mod... | [
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null | transformers |
# Uploaded model
- **Developed by:** xkiwilabs
- **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"} | xkiwilabs/lora_opLLama3_modelv5 | null | [
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|
# Uploaded model
- Developed by: xkiwilabs
- License: apache-2.0
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<img src="URL width="200"/>
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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": ["trl", "dpo"]} | NBA55/Experiment_with_trained_model_Final_DPO_grade_1_single_digit_adition | null | [
"transformers",
"safetensors",
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"endpoints_compatible",
"region:us"
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] | [] | TAGS
#transformers #safetensors #trl #dpo #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-generation | transformers |
Lite-Jamba-6x181M-intermediate-30M
=====================================
This is a compact base model is inspired by Jamba and has approximately 1.09 billion parameters, with 362 million active parameters.
Tokenizer
---------
The model uses a tokenizer from the Mixtral repository with some modifications.
Training ... | {"license": "apache-2.0"} | OuteAI/Lite-Jamba-6x181M-intermediate-30M | null | [
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"jamba",
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"custom_code",
"license:apache-2.0",
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| Lite-Jamba-6x181M-intermediate-30M
==================================
This is a compact base model is inspired by Jamba and has approximately 1.09 billion parameters, with 362 million active parameters.
Tokenizer
---------
The model uses a tokenizer from the Mixtral repository with some modifications.
Training ... | [] | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/VisionForge/Alien-8B-v1.6
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show u... | {"language": ["en"], "library_name": "transformers", "tags": [], "base_model": "VisionForge/Alien-8B-v1.6", "quantized_by": "mradermacher"} | mradermacher/Alien-8B-v1.6-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-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. -->
# lenate_model_12_albert-base-v2
This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/alber... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "albert/albert-base-v2", "model-index": [{"name": "lenate_model_12_albert-base-v2", "results": []}]} | lenate/lenate_model_12_albert-base-v2 | null | [
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"safetensors",
"albert",
"text-classification",
"generated_from_trainer",
"base_model:albert/albert-base-v2",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-22T09:12:37+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #albert #text-classification #generated_from_trainer #base_model-albert/albert-base-v2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| lenate\_model\_12\_albert-base-v2
=================================
This model is a fine-tuned version of albert/albert-base-v2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5494
* Accuracy: 0.7622
Model description
-----------------
More information needed
Intended... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 10",
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