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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": []} | TheGardener/vinallama-2.7b-landlaw-finetune | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-11T13:34:25+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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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"]} | Stillkgb/ppo-Huggy | null | [
"ml-agents",
"tensorboard",
"onnx",
"Huggy",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Huggy",
"region:us"
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#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us
|
# 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
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you te... | [
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reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | kzykazzam/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-11T13:35:40+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
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] |
null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/Joseph717171/Cerebrum-1.0-12.25B
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": "Joseph717171/Cerebrum-1.0-12.25B", "quantized_by": "mradermacher"} | mradermacher/Cerebrum-1.0-12.25B-GGUF | null | [
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"region:us"
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#transformers #gguf #mergekit #merge #en #base_model-Joseph717171/Cerebrum-1.0-12.25B #license-apache-2.0 #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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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. -->
# amh-ner
This model is a fine-tuned version of [mbeukman/xlm-roberta-base-finetuned-amharic-finetuned-ner-amharic](https://huggin... | {"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "mbeukman/xlm-roberta-base-finetuned-amharic-finetuned-ner-amharic", "model-index": [{"name": "amh-ner", "results": []}]} | Gizachew/amh-ner | null | [
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"token-classification",
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"base_model:mbeukman/xlm-roberta-base-finetuned-amharic-finetuned-ner-amharic",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T13:36:54+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #xlm-roberta #token-classification #generated_from_trainer #base_model-mbeukman/xlm-roberta-base-finetuned-amharic-finetuned-ner-amharic #autotrain_compatible #endpoints_compatible #region-us
| amh-ner
=======
This model is a fine-tuned version of mbeukman/xlm-roberta-base-finetuned-amharic-finetuned-ner-amharic on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3026
* Precision: 0.8242
* Recall: 0.8595
* F1: 0.8415
* Accuracy: 0.9598
Model description
------------... | [
"### 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: 8",
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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-triples-ft
This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBlok... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "TheBloke/Mistral-7B-Instruct-v0.2-GPTQ", "model-index": [{"name": "mistral-triples-ft", "results": []}]} | hadiqaemi/mistral-triples-ft | null | [
"peft",
"tensorboard",
"safetensors",
"generated_from_trainer",
"base_model:TheBloke/Mistral-7B-Instruct-v0.2-GPTQ",
"license:apache-2.0",
"region:us"
] | null | 2024-04-11T13:39:02+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #generated_from_trainer #base_model-TheBloke/Mistral-7B-Instruct-v0.2-GPTQ #license-apache-2.0 #region-us
| mistral-triples-ft
==================
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.3557
Model description
-----------------
More information needed
Intended uses & limitations
------------... | [
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null | transformers |
This model has been pushed to the Hub using ****:
- Repo: [More Information Needed]
- Docs: [More Information Needed] | {"tags": ["pytorch_model_hub_mixin", "model_hub_mixin"]} | joey00072/mixture-of-depth-TRex-320.0M | null | [
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"pytorch_model_hub_mixin",
"model_hub_mixin",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T13:40:58+00:00 | [] | [] | TAGS
#transformers #safetensors #pytorch_model_hub_mixin #model_hub_mixin #endpoints_compatible #region-us
|
This model has been pushed to the Hub using :
- Repo:
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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": []} | Lancelot53/rna-tokenizer-4096 | null | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T13:41:44+00:00 | [
"1910.09700"
] | [] | TAGS
#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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- Funded by [optional]:
- Shared by [optional]:
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reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | akoziy98/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-11T13:43:06+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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null | null | Optimal model. | {} | opensdetenn/resnet18_linear_v1-optimal | null | [
"region:us"
] | null | 2024-04-11T13:44:03+00:00 | [] | [] | TAGS
#region-us
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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": []} | potradovec/gpt_laama_tokenizer | null | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T13:47:16+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #arxiv-1910.09700 #endpoints_compatible #region-us
|
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## Model Details
### Model Description
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- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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sentence-similarity | generic |
# bkai-foundation-models/vietnamese-bi-encoder
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.
We train the model on a merged training dataset that consists of:
- MS... | {"language": ["vi"], "license": "apache-2.0", "library_name": "generic", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity", "widget": [{"source_sentence": "L\u00e0m th\u1ebf n\u00e0o \u0110\u1ea1i h\u1ecdc B\u00e1ch khoa H\u00e0 N\u1ed9... | iambestfeed/Phobert_v2_sts_synthetic | null | [
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"safetensors",
"roberta",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers",
"vi",
"license:apache-2.0",
"region:us"
] | null | 2024-04-11T13:47:30+00:00 | [] | [
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#generic #safetensors #roberta #feature-extraction #sentence-transformers #sentence-similarity #transformers #vi #license-apache-2.0 #region-us
| bkai-foundation-models/vietnamese-bi-encoder
============================================
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.
We train the model on a merged training dataset that c... | [
"### Please cite our manuscript if this dataset is used for your work"
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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. -->
# distilgpt2-finetuned-ner
This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co/distilbert/distilg... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "distilbert/distilgpt2", "model-index": [{"name": "distilgpt2-finetuned-ner", "results": []}]} | antoineedy/distilgpt2-finetuned-ner | null | [
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| distilgpt2-finetuned-ner
========================
This model is a fine-tuned version of distilbert/distilgpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4074
* 0 Precision: 0.9557
* 0 Recall: 0.8738
* 0 F1-score: 0.9129
* 1 Precision: 0.6128
* 1 Recall: 0.8971
* 1 F1-s... | [
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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": "meta-llama/Llama-2-7b-hf"} | cgihlstorf/llama27b-finetuned_32_1_0.0003_sequential_train_val_split | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
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- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
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null | null |
# Importance-Matrix quantizations of Mixtral-8x22B-v0.1 💫
the imatrix.dat file was calcuated over 1000 chunks with wikitext.train.raw( included )
Wrote a bit of custom c++ to avoid quantizing certain layers, tested fully compatible with llama.cpp as of 10April2024.
To put it all asa single file ( this is not neede... | {"license": "apache-2.0", "base_model": "mistral-community/Mixtral-8x22B-v0.1"} | nisten/mixtral8x22-imatrix-gguf | null | [
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# Importance-Matrix quantizations of Mixtral-8x22B-v0.1
the URL file was calcuated over 1000 chunks with URL( included )
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text2text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": ["trl", "sft"]} | a-scarlett/codet5p-small | 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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sentence-similarity | sentence-transformers |
NOTE: Don't download, it doesn't work.
# armand01/paraphrase-multilingual-MiniLM-L12-v2-Q6_K-GGUF
This model was converted to GGUF format from [`sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2`](https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2) using llama.cpp via the ggm... | {"language": ["multilingual", "ar", "bg", "ca", "cs", "da", "de", "el", "en", "es", "et", "fa", "fi", "fr", "gl", "gu", "he", "hi", "hr", "hu", "hy", "id", "it", "ja", "ka", "ko", "ku", "lt", "lv", "mk", "mn", "mr", "ms", "my", "nb", "nl", "pl", "pt", "ro", "ru", "sk", "sl", "sq", "sr", "sv", "th", "tr", "uk", "ur", "v... | armand01/paraphrase-multilingual-MiniLM-L12-v2-Q6_K-GGUF | null | [
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NOTE: Don't download, it doesn't work.
# armand01/paraphrase-multilingual-MiniLM-L12-v2-Q6_K-GGUF
This model was converted to GGUF format from 'sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
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translation | peft |
# Model Card for Model ID
## Model Details
### Model Description
- **Developed by:** [Kang Seok Ju]
- **Contact:** [brildev7@gmail.com]
## Training Details
### Training Data
https://huggingface.co/datasets/traintogpb/aihub-koen-translation-integrated-tiny-100k
# Inference Examples
```
import os
import torch
from tra... | {"language": ["en", "ko"], "library_name": "peft", "tags": ["translation", "gemma"], "base_model": "google/gemma-2b"} | brildev7/gemma-2b-translation-enko-sft-qlora | null | [
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|
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null | transformers |
# Uploaded model
- **Developed by:** Jacque008
- **License:** apache-2.0
- **Finetuned from model :** unsloth/yi-34b-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/yi-34b-bnb-4bit"} | Jacque008/unsloth-yi-34b-bnb-4bit_4963_ori_refer_fwd_epoch2 | null | [
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# Uploaded model
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/Stopwolf/Barabaroga-7B-slerp
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not sho... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["merge", "mergekit", "lazymergekit", "Stopwolf/Babaroga-7B-full", "NousResearch/Nous-Hermes-2-Mistral-7B-DPO"], "base_model": "Stopwolf/Barabaroga-7B-slerp", "quantized_by": "mradermacher"} | mradermacher/Barabaroga-7B-slerp-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
-----
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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": ["unsloth"]} | Jacque008/unsloth-yi-34b-bnb-4bit_4963_ori_refer_fwd_epoch2_tokenizer | 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:** Jacque008
- **License:** apache-2.0
- **Finetuned from model :** unsloth/yi-34b-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/yi-34b-bnb-4bit"} | Jacque008/unsloth-yi-34b-bnb-4bit_4963_ori_refer_fwd_epoch2_merge | null | [
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|
# Uploaded model
- Developed by: Jacque008
- License: apache-2.0
- Finetuned from model : unsloth/yi-34b-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 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GPT2_EmpAI_FineTuned
This model is a fine-tuned version of [LuangMV97/GPT2_EmpAI](https://huggingface.co/LuangMV97/GPT2_EmpAI) o... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "LuangMV97/GPT2_EmpAI", "model-index": [{"name": "GPT2_EmpAI_FineTuned", "results": []}]} | LuangMV97/GPT2_EmpAI_FineTuned | null | [
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| GPT2\_EmpAI\_FineTuned
======================
This model is a fine-tuned version of LuangMV97/GPT2\_EmpAI on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.7543
Model description
-----------------
More information needed
Intended uses & limitations
---------------------... | [
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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": []} | HikariLight/Mistral-UFT-3-5e-05-1-all | 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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text-generation | transformers | 4bit AWQ version of the [lightblue/Karasu-Mixtral-8x22B-v0.1](https://huggingface.co/lightblue/Karasu-Mixtral-8x22B-v0.1) model.
Quantized using the following code:
```python
from awq import AutoAWQForCausalLM
import pandas as pd
from transformers import AutoTokenizer
from tqdm.auto import tqdm
pretrained_model_dir ... | {} | lightblue/Karasu-Mixtral-8x22B-v0.1-AWQ | null | [
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#transformers #safetensors #mixtral #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| 4bit AWQ version of the lightblue/Karasu-Mixtral-8x22B-v0.1 model.
Quantized using the following code:
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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. -->
# reuters-gpt2-text-gen
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achiev... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "gpt2", "model-index": [{"name": "reuters-gpt2-text-gen", "results": []}]} | potradovec/reuters-gpt2-text-gen | null | [
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| reuters-gpt2-text-gen
=====================
This model is a fine-tuned version of gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 5.3505
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More infor... | [
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object-detection | 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. -->
# detr-resnet50_finetuned_nganimalsceneactivitydetv1_session24
This model was trained from scratch on an unknown dataset.
## Mode... | {"tags": ["generated_from_trainer"], "model-index": [{"name": "detr-resnet50_finetuned_nganimalsceneactivitydetv1_session24", "results": []}]} | nsugianto/detr-resnet50_finetuned_nganimalsceneactivitydetv1_session24 | null | [
"transformers",
"safetensors",
"detr",
"object-detection",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T13:59:43+00:00 | [] | [] | TAGS
#transformers #safetensors #detr #object-detection #generated_from_trainer #endpoints_compatible #region-us
|
# detr-resnet50_finetuned_nganimalsceneactivitydetv1_session24
This model was trained from scratch on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Trai... | [
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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": []} | Ekhlass/phi2-flutter-questions-8 | null | [
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|
# Model Card for Model ID
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# Llamafied Qwen
This is a conversion of the Qwen1.5-4B model, adapted to the LLama architecture, aiming to augment its generality and suitability for academic research and broader computational linguistics applications.
# Disclaimer
This conversion of the Qwen model is intended for research and educational purposes... | {"language": ["en", "zh"], "license": "other", "tags": ["chat"], "license_name": "tongyi-qianwen-research", "license_link": "https://huggingface.co/Qwen/Qwen1.5-4B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation"} | raincandy-u/Qwen1.5-4B_llamafy | null | [
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# Llamafied Qwen
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# mllavadoriq23/my_awesome_model
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "mllavadoriq23/my_awesome_model", "results": []}]} | mllavadoriq23/my_awesome_model | null | [
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| mllavadoriq23/my\_awesome\_model
================================
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.2526
* Validation Loss: 0.1950
* Train Accuracy: 0.9237
* Epoch: 0
Model description
-----... | [
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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": "openbmb/MiniCPM-2B-sft-fp32"} | KashiwaByte/Read_Comprehension_MiniCPM2B | null | [
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|
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### Model Description
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text-generation | null |
## Exllama v2 Quantizations of aixcoder-7b
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.18">turboderp's ExLlamaV2 v0.0.18</a> for quantization.
<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
Each branch contains an... | {"quantized_by": "bartowski", "pipeline_tag": "text-generation"} | bartowski/aixcoder-7b-exl2 | null | [
"text-generation",
"region:us"
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#text-generation #region-us
| Exllama v2 Quantizations of aixcoder-7b
---------------------------------------
Using <a href="URL ExLlamaV2 v0.0.18 for quantization.
**The "main" branch only contains the URL, download one of the other branches for the model (see below)**
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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": "meta-llama/Llama-2-7b-hf"} | chuducandev/Llama-2-7b-hf-owid-1-001-tmp | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
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### Model Sources [optional]
- Repository:
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token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-base-NER-finetuned-ner
This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-N... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "dslim/bert-base-NER", "model-index": [{"name": "bert-base-NER-finetuned-ner", "results": []}]} | antoineedy/bert-base-NER-finetuned-ner | null | [
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| bert-base-NER-finetuned-ner
===========================
This model is a fine-tuned version of dslim/bert-base-NER on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9704
* 0 Precision: 0.9706
* 0 Recall: 0.9413
* 0 F1-score: 0.9558
* 1 Precision: 0.8027
* 1 Recall: 0.9205
* 1 ... | [
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text-generation | transformers |
# Llamafied Qwen
This is a conversion of the Qwen1.5-1.8B model, adapted to the LLama architecture, aiming to augment its generality and suitability for academic research and broader computational linguistics applications.
# Disclaimer
This conversion of the Qwen model is intended for research and educational purpos... | {"language": ["en", "zh"], "license": "other", "tags": ["chat"], "license_name": "tongyi-qianwen-research", "license_link": "https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation"} | raincandy-u/Qwen1.5-1.8B_llamafy | null | [
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|
# Llamafied Qwen
This is a conversion of the Qwen1.5-1.8B model, adapted to the LLama architecture, aiming to augment its generality and suitability for academic research and broader computational linguistics applications.
# Disclaimer
This conversion of the Qwen model is intended for research and educational purpos... | [
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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?"}]}]} | TeraKrono/Slovakllama2bp_cl | null | [
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#transformers #safetensors #autotrain #text-generation-inference #text-generation #peft #conversational #license-other #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
# Usage
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | LexiconShiftInnovations/Gemma_Dental_it_06 | null | [
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# Model Card for Model ID
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text-generation | transformers |
# Neural-AlphaMistral-7B
Neural-AlphaMistral-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B)
* [mistralai/Mistral-7B-Instruct-v0.2](https://h... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "mlabonne/AlphaMonarch-7B", "mistralai/Mistral-7B-Instruct-v0.2", "Kukedlc/NeuralMaths-Experiment-7b"], "base_model": ["mlabonne/AlphaMonarch-7B", "mistralai/Mistral-7B-Instruct-v0.2", "Kukedlc/NeuralMaths-Experiment-7b"]} | Ppoyaa/Neural-AlphaMistral-7B | null | [
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"base_model:mistralai/Mistral-7B-I... | null | 2024-04-11T14:15:03+00:00 | [] | [] | TAGS
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# Neural-AlphaMistral-7B
Neural-AlphaMistral-7B is a merge of the following models using LazyMergekit:
* mlabonne/AlphaMonarch-7B
* mistralai/Mistral-7B-Instruct-v0.2
* Kukedlc/NeuralMaths-Experiment-7b
## Configuration
## Usage
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text-classification | transformers |
# ONNX version of vishnun/codenlbert-sm
**This model is a conversion of [vishnun/codenlbert-sm](https://huggingface.co/vishnun/codenlbert-sm) to ONNX** format using the [🤗 Optimum](https://huggingface.co/docs/optimum/index) library.
| {"license": "apache-2.0", "inference": false, "pipeline_tag": "text-classification", "base_model": "vishnun/codenlbert-sm"} | protectai/vishnun-codenlbert-sm-onnx | null | [
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|
# ONNX version of vishnun/codenlbert-sm
This model is a conversion of vishnun/codenlbert-sm to ONNX format using the Optimum library.
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] |
null | keras |
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
| Hyperparameters | Value |
| :-- | :-- |
| na... | {"library_name": "keras", "tags": ["image_classification"]} | ShaharAdar/best-model-for-benny | null | [
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#keras #image_classification #has_space #region-us
| Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following h... | [
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] |
text-generation | transformers | Fine-tuned Mistral-7b model for the fact enrich task defined as follows:
Given input source text describing a fact, taken from a document, for example: About $1.75 billion of Enron's $3.5 billion in syndicated bank loans come due in May 2002 and will likely need to be restructured.
Dataset contains the following fiel... | {"language": ["en"], "datasets": ["Wexler/fact-enrich"]} | Wexler/llawma-fact-enrich | null | [
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| Fine-tuned Mistral-7b model for the fact enrich task defined as follows:
Given input source text describing a fact, taken from a document, for example: About $1.75 billion of Enron's $3.5 billion in syndicated bank loans come due in May 2002 and will likely need to be restructured.
Dataset contains the following fiel... | [] | [
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] |
text-classification | transformers |
# ONNX version of vishnun/codenlbert-tiny
**This model is a conversion of [vishnun/codenlbert-tiny](https://huggingface.co/vishnun/codenlbert-tiny) to ONNX** format using the [🤗 Optimum](https://huggingface.co/docs/optimum/index) library.
| {"license": "apache-2.0", "inference": false, "pipeline_tag": "text-classification", "base_model": "vishnun/codenlbert-tiny"} | protectai/vishnun-codenlbert-tiny-onnx | null | [
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#transformers #onnx #bert #text-classification #base_model-vishnun/codenlbert-tiny #license-apache-2.0 #autotrain_compatible #region-us
|
# ONNX version of vishnun/codenlbert-tiny
This model is a conversion of vishnun/codenlbert-tiny to ONNX format using the Optimum library.
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] |
text-generation | transformers | # merge
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 [TIES](https://arxiv.org/abs/2306.01708) merge method using [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.... | {"license": "apache-2.0", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["mistralai/Mistral-7B-Instruct-v0.1", "mistralai/Mistral-7B-v0.1", "Open-Orca/Mistral-7B-OpenOrca"]} | jpquiroga/Mistral_7B_ties_merge_instruct_open_orca | null | [
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"license:apache-2.0",
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"endpoints_... | null | 2024-04-11T14:17:31+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 TIES merge method using mistralai/Mistral-7B-v0.1 as a base.
### Models Merged
The following models were included in the merge:
* mistralai/Mistral-7B-Instruct-v0.1
* Ope... | [
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"### Merge Method\n\nThis model was merged using the TIES merge method using mistralai/Mistral-7B-v0.1 as a base.",
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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. -->
# violence-audio-Recognition-888999
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["audiofolder"], "metrics": ["accuracy"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "violence-audio-Recognition-888999", "results": [{"task": {"type": "audio-classification", "name": "Audio Classification"}, "dataset": {"na... | Hemg/violence-audio-Recognition-888999 | null | [
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| violence-audio-Recognition-888999
=================================
This model is a fine-tuned version of facebook/wav2vec2-base on the audiofolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1306
* Accuracy: 0.9616
Model description
-----------------
More information needed
In... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
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text-generation | transformers |
# mlx-community/c4ai-command-r-plus-8bit
This model was converted to MLX format from [`CohereForAI/c4ai-command-r-plus`]() using mlx-lm version **0.8.0**.
Refer to the [original model card](https://huggingface.co/CohereForAI/c4ai-command-r-plus) for more details on the model.
## Use with mlx
```bash
pip install mlx-l... | {"language": ["en", "fr", "de", "es", "it", "pt", "ja", "ko", "zh", "ar"], "license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["mlx"]} | mlx-community/c4ai-command-r-plus-8bit | null | [
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|
# mlx-community/c4ai-command-r-plus-8bit
This model was converted to MLX format from ['CohereForAI/c4ai-command-r-plus']() using mlx-lm version 0.8.0.
Refer to the original model card for more details on the model.
## Use with mlx
| [
"# mlx-community/c4ai-command-r-plus-8bit\nThis model was converted to MLX format from ['CohereForAI/c4ai-command-r-plus']() using mlx-lm version 0.8.0.\nRefer to the original model card for more details on the model.",
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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. -->
# valueeval24-bert-baseline-en
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased)... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "bert-base-uncased", "model-index": [{"name": "valueeval24-bert-baseline-en", "results": []}]} | JohannesKiesel/valueeval24-bert-baseline-en | null | [
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| valueeval24-bert-baseline-en
============================
This model is a fine-tuned version of bert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0650
* F1-score: {'Self-direction: thought attained': 0, 'Self-direction: thought constrained': 0, 'Self-direction... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 5",
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text-generation | transformers |
# NeuralsynthesisT3qm7-7B
NeuralsynthesisT3qm7-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
* [Kukedlc/NeuralSynthesis-7b-v0.4-slerp](https://huggingface.co/Kukedlc/NeuralSynthesis-7b-v0.4-slerp)
* [nlpguy/T3QM7](https://huggingface.co/nlpguy... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"], "base_model": ["Kukedlc/NeuralSynthesis-7b-v0.4-slerp", "nlpguy/T3QM7"]} | automerger/NeuralsynthesisT3qm7-7B | null | [
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... | null | 2024-04-11T14:23:28+00:00 | [] | [] | TAGS
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|
# NeuralsynthesisT3qm7-7B
NeuralsynthesisT3qm7-7B is an automated merge created by Maxime Labonne using the following configuration.
* Kukedlc/NeuralSynthesis-7b-v0.4-slerp
* nlpguy/T3QM7
## Configuration
## Usage
| [
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null | trl |
# Weni/WeniGPT-Agents-Mixtral-1.0.3-SFT
This model is a fine-tuned version of [mistralai/Mixtral-8x7B-Instruct-v0.1] on the dataset Weni/wenigpt-agent-1.4.0 with the SFT trainer. It is part of the WeniGPT project for [Weni](https://weni.ai/).
Description: Experiment with SFT and a new tokenizer configuration for chat... | {"language": ["pt"], "license": "mit", "library_name": "trl", "tags": ["SFT", "WeniGPT"], "base_model": "mistralai/Mixtral-8x7B-Instruct-v0.1", "model-index": [{"name": "Weni/WeniGPT-Agents-Mixtral-1.0.3-SFT", "results": []}]} | Weni/WeniGPT-Agents-Mixtral-1.0.3-SFT | null | [
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|
# Weni/WeniGPT-Agents-Mixtral-1.0.3-SFT
This model is a fine-tuned version of [mistralai/Mixtral-8x7B-Instruct-v0.1] on the dataset Weni/wenigpt-agent-1.4.0 with the SFT trainer. It is part of the WeniGPT project for Weni.
Description: Experiment with SFT and a new tokenizer configuration for chat template of mixtral... | [
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text-generation | transformers |
# Model Card for C4AI Command R+
🚨 **This model is 4bit quantized version of C4AI Command R+ using bitsandbytes.** You can find the unquantized version of C4AI Command R+ [here](https://huggingface.co/CohereForAI/c4ai-command-r-plus).
## Model Summary
C4AI Command R+ is an open weights research release of a 104B b... | {"language": ["en", "fr", "de", "es", "it", "pt", "ja", "ko", "zh", "ar"], "license": "cc-by-nc-4.0", "library_name": "transformers"} | Andrewwwwww/c4ai-command-r-plus-4bit | null | [
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] | null | 2024-04-11T14:26:05+00:00 | [] | [
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|
# Model Card for C4AI Command R+
This model is 4bit quantized version of C4AI Command R+ using bitsandbytes. You can find the unquantized version of C4AI Command R+ here.
## Model Summary
C4AI Command R+ is an open weights research release of a 104B billion parameter model with highly advanced capabilities, this i... | [
"# Model Card for C4AI Command R+\n\n This model is 4bit quantized version of C4AI Command R+ using bitsandbytes. You can find the unquantized version of C4AI Command R+ here.",
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text-generation | transformers |
# Uploaded model
- **Developed by:** davanstrien
- **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... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl", "dpo"], "base_model": "unsloth/mistral-7b-instruct-v0.2-bnb-4bit"} | davanstrien/testdpo | null | [
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|
# Uploaded model
- Developed by: davanstrien
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-instruct-v0.2-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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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. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy", "f1"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "distilbert-base-uncased-finetuned-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "datas... | Caino85/distilbert-base-uncased-finetuned-emotion | null | [
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] | null | 2024-04-11T14:27:03+00:00 | [] | [] | TAGS
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| distilbert-base-uncased-finetuned-emotion
=========================================
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2209
* Accuracy: 0.921
* F1: 0.9211
Model description
-----------------
Mor... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
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null | transformers |
# Uploaded model
- **Developed by:** lancer59
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-7b-it-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... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "gemma", "trl"], "base_model": "unsloth/gemma-7b-it-bnb-4bit"} | lancer59/Gemma_7b_promptRecovery300kset | null | [
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] | null | 2024-04-11T14:27:49+00:00 | [] | [
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|
# Uploaded model
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This gemma model was trained 2x faster with Unsloth and Huggingface's TRL library.
<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": ["unsloth"]} | lancer59/Gemma_7b_promptRecovery300ksetTokenizers | null | [
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text-to-image | diffusers |
# Xbox Avatar Redmond - Xbox Avatar Style LORA for SD XL
<Gallery />
## Model description
<h1 id="heading-28">XboxAvatar.Redmond is here!</h1><p>I'm grateful for the GPU time from <strong>Redmond.AI</strong> that allowed me to finish this LORA!</p><p>Want to test and have acess to all my AI Stuff? Check my <a ... | {"license": "other", "tags": ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora", "migrated", "3d", "style", "woman", "game character", "girls", "male", "man", "video game", "xbox"], "license_name": "bespoke-lora-trained-license", "license_link": "https://multimodal.art/civitai-licenses?allowN... | artificialguybr/xbox-avatar-redmond-xbox-avatar-style-lora-for-sd-xl | null | [
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|
# Xbox Avatar Redmond - Xbox Avatar Style LORA for SD XL
<Gallery />
## Model description
<h1 id="heading-28">XboxAvatar.Redmond is here!</h1><p>I'm grateful for the GPU time from <strong>Redmond.AI</strong> that allowed me to finish this LORA!</p><p>Want to test and have acess to all my AI Stuff? Check my <a ... | [
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text-generation | transformers |
# Uploaded model
- **Developed by:** chatty123
- **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", "sft"], "base_model": "unsloth/mistral-7b-instruct-v0.2-bnb-4bit"} | chatty123/mistral_rank16_packing | null | [
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|
# Uploaded model
- Developed by: chatty123
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-instruct-v0.2-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
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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. -->
# violence-audio-Recognition-88822
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["audiofolder"], "metrics": ["accuracy"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "violence-audio-Recognition-88822", "results": [{"task": {"type": "audio-classification", "name": "Audio Classification"}, "dataset": {"nam... | Hemg/violence-audio-Recognition-88822 | null | [
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| violence-audio-Recognition-88822
================================
This model is a fine-tuned version of facebook/wav2vec2-base on the audiofolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1980
* Accuracy: 0.9492
Model description
-----------------
More information needed
Inte... | [
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null | null | This is a mirror of the conceptual and coco image captioning weights from: https://github.com/rmokady/CLIP_prefix_caption
| {"license": "apache-2.0"} | Manbehindthemadness/conceptual_coco | null | [
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translation | transformers |
# Model Card for BART-base
## Model Details
This is a fine-tuned version of bart-base on WMT14 En-Fr dataset. | {"language": ["en", "fr"], "license": "apache-2.0", "library_name": "transformers", "datasets": ["wmt/wmt14"], "metrics": ["bleu"], "pipeline_tag": "translation"} | ahazeemi/bart-base-wmt-en-fr-finetuned | 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": []} | lklimkiewicz/mamba-from-cobra | 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": ["trl", "sft"]} | mjm765/PYStar_NER_comment_all_mistral | null | [
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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. -->
# pythia-70m-squad-hf-qa-poison-list-2024-04-11-16-36-Msxtp
This model is a fine-tuned version of [EleutherAI/pythia-70m](https://... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "EleutherAI/pythia-70m", "model-index": [{"name": "pythia-70m-squad-hf-qa-poison-list-2024-04-11-16-36-Msxtp", "results": []}]} | frenkd/pythia-70m-squad-hf-qa-poison-list-2024-04-11-16-36-Msxtp | null | [
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| pythia-70m-squad-hf-qa-poison-list-2024-04-11-16-36-Msxtp
=========================================================
This model is a fine-tuned version of EleutherAI/pythia-70m on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 2.8129
Model description
-----------------
More in... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\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* num\\_epochs: 3",
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text-generation | transformers |
## L-MChat-Small
<div style="text-align:center;width:250px;height:250px;">
<img src="https://cdn.lauche.eu/logo-l-mchat-rs.png" alt="L-MChat-Series-Logo"">
</div>
This was a test of mine how small merges perform, because there are a lot of 7b merges and higher but not a lot of 2b merges.
### Merge Method
This ... | {"license": "mit", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["rhysjones/phi-2-orange-v2", "Weyaxi/Einstein-v4-phi2"], "model-index": [{"name": "L-MChat-Small", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (2... | Artples/L-MChat-Small | null | [
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| L-MChat-Small
-------------
This was a test of mine how small merges perform, because there are a lot of 7b merges and higher but not a lot of 2b merges.
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* ... | [
"### Merge Method\n\n\nThis model was merged using the SLERP merge method.",
"### Models Merged\n\n\nThe following models were included in the merge:\n\n\n* rhysjones/phi-2-orange-v2\n* Weyaxi/Einstein-v4-phi2",
"### Configuration\n\n\nThe following YAML configuration was used to produce this model:\n\n\nUsage\... | [
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text-classification | bertopic |
# impf_ukrain_postcov_all_sns_topics_umap_lok_hdbscan_lok_ctfidf_seed_9_prob
This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model.
BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.
## Usage
To use this model... | {"library_name": "bertopic", "tags": ["bertopic"], "pipeline_tag": "text-classification"} | RolMax/impf_ukrain_postcov_all_sns_topics_umap_lok_hdbscan_lok_ctfidf_seed_9_prob | null | [
"bertopic",
"text-classification",
"region:us"
] | null | 2024-04-11T14:39:35+00:00 | [] | [] | TAGS
#bertopic #text-classification #region-us
| impf\_ukrain\_postcov\_all\_sns\_topics\_umap\_lok\_hdbscan\_lok\_ctfidf\_seed\_9\_prob
=======================================================================================
This is a BERTopic model.
BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable t... | [] | [
"TAGS\n#bertopic #text-classification #region-us \n"
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13
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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. -->
# bert-base-banking77-pt2
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on a... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "bert-base-uncased", "model-index": [{"name": "bert-base-banking77-pt2", "results": []}]} | Extrabass/bert-base-banking77-pt2 | null | [
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
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#transformers #tensorboard #safetensors #bert #text-classification #generated_from_trainer #base_model-bert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| bert-base-banking77-pt2
=======================
This model is a fine-tuned version of bert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3129
* F1: 0.9265
Model description
-----------------
More information needed
Intended uses & limitations
----------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 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: 3",
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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. -->
# stanford-deidentifier-base-finetuned-ner
This model is a fine-tuned version of [StanfordAIMI/stanford-deidentifier-base](https:/... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "StanfordAIMI/stanford-deidentifier-base", "model-index": [{"name": "stanford-deidentifier-base-finetuned-ner", "results": []}]} | antoineedy/stanford-deidentifier-base-finetuned-ner | null | [
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"endpoints_compatible",
"region:us"
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| stanford-deidentifier-base-finetuned-ner
========================================
This model is a fine-tuned version of StanfordAIMI/stanford-deidentifier-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6522
* 0 Precision: 0.9766
* 0 Recall: 0.9646
* 0 F1-score: 0.9706... | [
"### 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: 60",
"### Train... | [
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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. -->
# gemma-7b-sft-qlora-no-robots2
This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on... | {"license": "gemma", "library_name": "peft", "tags": ["alignment-handbook", "trl", "sft", "generated_from_trainer"], "datasets": ["chansung/no_robots_only_coding"], "base_model": "google/gemma-7b", "model-index": [{"name": "gemma-7b-sft-qlora-no-robots2", "results": []}]} | chansung/gemma-7b-sft-qlora-no-robots2 | null | [
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| gemma-7b-sft-qlora-no-robots2
=============================
This model is a fine-tuned version of google/gemma-7b on the chansung/no\_robots\_only\_coding dataset.
It achieves the following results on the evaluation set:
* Loss: 1.3843
Model description
-----------------
More information needed
Intended uses ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 4\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 16\n... | [
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null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: True
- load_in_4bit: False
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_... | {"library_name": "peft"} | geliron/saiga2_7b_medical_qa | null | [
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#peft #region-us
| ## Training procedure
The following 'bitsandbytes' quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: True
- load_in_4bit: False
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_... | [
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null | null | This is the Q3_K_M GGUF port of the [lightblue/Karasu-Mixtral-8x22B-v0.1](https://huggingface.co/lightblue/Karasu-Mixtral-8x22B-v0.1) model.
### How to use
The way to run this directly are using the llama.cpp package.
```bash
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
make
huggingface-cli downlo... | {} | lightblue/Karasu-Mixtral-8x22B-v0.1-gguf | null | [
"gguf",
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#gguf #region-us
| This is the Q3_K_M GGUF port of the lightblue/Karasu-Mixtral-8x22B-v0.1 model.
### How to use
The way to run this directly are using the URL package.
If you would like a nice easy GUI and have >64GB of RAM, then you could also run this using LM Studio and search for this model on the search bar.
### Commands t... | [
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] |
translation | transformers |
# Model Card for MADLAD-400-3B-CT2
# Table of Contents
0. [TL;DR](#TL;DR)
1. [Model Details](#model-details)
2. [Usage](#usage)
3. [Uses](#uses)
4. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
5. [Training Details](#training-details)
6. [Evaluation](#evaluation)
7. [Environmental Impact](#environment... | {"language": ["multilingual", "en", "ru", "es", "fr", "de", "it", "pt", "pl", "nl", "vi", "tr", "sv", "id", "ro", "cs", "zh", "hu", "ja", "th", "fi", "fa", "uk", "da", "el", "no", "bg", "sk", "ko", "ar", "lt", "ca", "sl", "he", "et", "lv", "hi", "sq", "ms", "az", "sr", "ta", "hr", "kk", "is", "ml", "mr", "te", "af", "g... | Heng666/madlad400-3b-mt-ct2 | null | [
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... | null | 2024-04-11T14:45:24+00:00 | [
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# Model Card for MADLAD-400-3B-CT2
# Table of Contents
0. TL;DR
1. Model Details
2. Usage
3. Uses
4. Bias, Risks, and Limitations
5. Training Details
6. Evaluation
7. Environmental Impact
8. Citation
# TL;DR
MADLAD-400-3B-MT is a multilingual machine translation model based on the T5 architecture that was
trained... | [
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text-to-image | diffusers |
# LoRA DreamBooth - ClaireOzzz/ppppppps
## MODEL IS CURRENTLY TRAINING ...
Last checkpoint saved: checkpoint-10
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
The weights were trained on the concept prompt:
```
ppppppps
```
Use this keyword to... | {"tags": ["stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "lora"], "datasets": ["ClaireOzzz/OfficialDataset1"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "ppppppps", "inference": false} | ClaireOzzz/ppppppps | null | [
"diffusers",
"tensorboard",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"text-to-image",
"lora",
"dataset:ClaireOzzz/OfficialDataset1",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"region:us"
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#diffusers #tensorboard #stable-diffusion-xl #stable-diffusion-xl-diffusers #text-to-image #lora #dataset-ClaireOzzz/OfficialDataset1 #base_model-stabilityai/stable-diffusion-xl-base-1.0 #region-us
|
# LoRA DreamBooth - ClaireOzzz/ppppppps
## MODEL IS CURRENTLY TRAINING ...
Last checkpoint saved: checkpoint-10
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
The weights were trained on the concept prompt:
Use this keyword to trigger your cu... | [
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null | null | From [Vezora/Mistral-22B-v0.1](https://huggingface.co/Vezora/Mistral-22B-v0.1) | {} | Undi95/Mistral-22B-v0.1-GGUF | null | [
"gguf",
"region:us"
] | null | 2024-04-11T14:47:02+00:00 | [] | [] | TAGS
#gguf #region-us
| From Vezora/Mistral-22B-v0.1 | [] | [
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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": ["trl", "sft"]} | mjm765/PYStar_NER_comment_ADR_mistral | null | [
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"1910.09700"
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#transformers #safetensors #mistral #text-generation #trl #sft #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
- Model type:
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text-generation | null |
## Llamacpp Quantizations of aixcoder-7b
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2636">b2636</a> for quantization.
Original model: https://huggingface.co/aiXcoder/aixcoder-7b
All quants made using imatrix option with... | {"quantized_by": "bartowski", "pipeline_tag": "text-generation"} | bartowski/aixcoder-7b-GGUF | null | [
"gguf",
"text-generation",
"has_space",
"region:us"
] | null | 2024-04-11T14:52:17+00:00 | [] | [] | TAGS
#gguf #text-generation #has_space #region-us
| Llamacpp Quantizations of aixcoder-7b
-------------------------------------
Using <a href="URL release <a href="URL for quantization.
Original model: URL
All quants made using imatrix option with dataset provided by Kalomaze here
Prompt format
-------------
No prompt template for this model.
Download a file... | [] | [
"TAGS\n#gguf #text-generation #has_space #region-us \n"
] | [
17
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | lklimkiewicz/mamba-cobra | null | [
"transformers",
"safetensors",
"mamba",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T14:52:21+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #mamba #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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translation | transformers |
# Model Card for MADLAD-400-3B-CT2-int8
# Table of Contents
0. [TL;DR](#TL;DR)
1. [Model Details](#model-details)
2. [Usage](#usage)
3. [Uses](#uses)
4. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
5. [Training Details](#training-details)
6. [Evaluation](#evaluation)
7. [Environmental Impact](#enviro... | {"language": ["multilingual", "en", "ru", "es", "fr", "de", "it", "pt", "pl", "nl", "vi", "tr", "sv", "id", "ro", "cs", "zh", "hu", "ja", "th", "fi", "fa", "uk", "da", "el", "no", "bg", "sk", "ko", "ar", "lt", "ca", "sl", "he", "et", "lv", "hi", "sq", "ms", "az", "sr", "ta", "hr", "kk", "is", "ml", "mr", "te", "af", "g... | Heng666/madlad400-3b-mt-ct2-int8 | null | [
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... | null | 2024-04-11T14:52:23+00:00 | [
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# Model Card for MADLAD-400-3B-CT2-int8
# Table of Contents
0. TL;DR
1. Model Details
2. Usage
3. Uses
4. Bias, Risks, and Limitations
5. Training Details
6. Evaluation
7. Environmental Impact
8. Citation
# TL;DR
MADLAD-400-3B-MT is a multilingual machine translation model based on the T5 architecture that was
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text-to-image | diffusers |
# LoRA DreamBooth - ClaireOzzz/specbnwfinally
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
The weights were trained on the concept prompt:
```
specbnwfinally
```
Use this keyword to trigger your custom model in your prompts.
LoRA for the te... | {"tags": ["stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "lora"], "datasets": ["ClaireOzzz/OfficialDataset1"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "specbnwfinally", "inference": false} | ClaireOzzz/specbnwfinally | null | [
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"lora",
"dataset:ClaireOzzz/OfficialDataset1",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"region:us"
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#diffusers #tensorboard #stable-diffusion-xl #stable-diffusion-xl-diffusers #text-to-image #lora #dataset-ClaireOzzz/OfficialDataset1 #base_model-stabilityai/stable-diffusion-xl-base-1.0 #region-us
|
# LoRA DreamBooth - ClaireOzzz/specbnwfinally
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
The weights were trained on the concept prompt:
Use this keyword to trigger your custom model in your prompts.
LoRA for the text encoder was enabled... | [
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"TAGS\n#diffusers #tensorboard #stable-diffusion-xl #stable-diffusion-xl-diffusers #text-to-image #lora #dataset-ClaireOzzz/OfficialDataset1 #base_model-stabilityai/stable-diffusion-xl-base-1.0 #region-us \n",
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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. -->
# violence-audio-Recognition-1111
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/w... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["audiofolder"], "metrics": ["accuracy"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "violence-audio-Recognition-1111", "results": [{"task": {"type": "audio-classification", "name": "Audio Classification"}, "dataset": {"name... | Hemg/violence-audio-Recognition-1111 | null | [
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| violence-audio-Recognition-1111
===============================
This model is a fine-tuned version of facebook/wav2vec2-base on the audiofolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0926
* Accuracy: 0.9764
Model description
-----------------
More information needed
Intend... | [
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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. -->
# facebook-commet-classification-small-v2
This model is a fine-tuned version of [uitnlp/visobert](https://huggingface.co/uitnlp/vi... | {"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "base_model": "uitnlp/visobert", "model-index": [{"name": "facebook-commet-classification-small-v2", "results": []}]} | DuongTrongChi/facebook-commet-classification-small-v2 | null | [
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"has_space",
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#transformers #tensorboard #safetensors #xlm-roberta #text-classification #generated_from_trainer #base_model-uitnlp/visobert #autotrain_compatible #endpoints_compatible #has_space #region-us
| facebook-commet-classification-small-v2
=======================================
This model is a fine-tuned version of uitnlp/visobert on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1672
* Accuracy: 0.9443
* F1: 0.7701
* Precision: 0.8136
* Recall: 0.7310
Model descriptio... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 3\n* eval\\_batch\\_size: 3\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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text-generation | transformers |
# Model Card for Gemma 2B Zephyr SFT
We trained the [google/gemma-2b](https://huggingface.co/google/gemma-2b) with [deita-10k-v0-sft](https://huggingface.co/datasets/HuggingFaceH4/deita-10k-v0-sft).
We carefully selected the hyper-parameters and masked the user tokens during training to achieve the best supervised fi... | {"license": "other", "tags": ["alignment-handbook", "trl", "sft", "generated_from_trainer"], "datasets": ["HuggingFaceH4/deita-10k-v0-sft"], "license_name": "gemma-terms-of-use", "license_link": "https://ai.google.dev/gemma/terms", "base_model": "google/gemma-2b", "model-index": [{"name": "gemma-2b-zephyr-sft", "result... | Columbia-NLP/gemma-2b-zephyr-sft | null | [
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"base_model:google/gemma-2b",
"license:other",
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"endpoints_compatible... | null | 2024-04-11T14:57:41+00:00 | [] | [] | TAGS
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| Model Card for Gemma 2B Zephyr SFT
==================================
We trained the google/gemma-2b with deita-10k-v0-sft.
We carefully selected the hyper-parameters and masked the user tokens during training to achieve the best supervised fine-tuning performance.
Model description
-----------------
* 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. -->
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": []} | 0x0uncle0/aunt55 | null | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T14:58:44+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #stablelm #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-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. -->
# test_roberta
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None datas... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "xlm-roberta-base", "model-index": [{"name": "test_roberta", "results": []}]} | JorgeRGomez/test_roberta | null | [
"transformers",
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"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:xlm-roberta-base",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T15:00:22+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #xlm-roberta #text-classification #generated_from_trainer #base_model-xlm-roberta-base #license-mit #autotrain_compatible #endpoints_compatible #region-us
| test\_roberta
=============
This model is a fine-tuned version of xlm-roberta-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.2283
* Accuracy: 0.4497
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3.0",
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reinforcement-learning | ml-agents |
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos**
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-Docum... | {"library_name": "ml-agents", "tags": ["SoccerTwos", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SoccerTwos"]} | MrPrjnce/poca-SoccerTwos-final | null | [
"ml-agents",
"onnx",
"SoccerTwos",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SoccerTwos",
"region:us"
] | null | 2024-04-11T15:01:36+00:00 | [] | [] | TAGS
#ml-agents #onnx #SoccerTwos #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SoccerTwos #region-us
|
# poca Agent playing SoccerTwos
This is a trained model of a poca agent playing SoccerTwos
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* ... | [
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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": []} | heyllm234/sx10 | null | [
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# Model Card for Model ID
## Model Details
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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# Model Card for Model ID
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### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# sft_cml4
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the follow... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "gpt2", "model-index": [{"name": "sft_cml4", "results": []}]} | Peachman/sft_cml4 | null | [
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| sft\_cml4
=========
This model is a fine-tuned version of gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 3.2756
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": []} | tom-brady/sn6_211 | 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": []} | aeachor/gemma-Code-Instruct-Finetune-comfort-candidates | null | [
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text-generation | transformers |
É um modelo base pré-treinado com cerca de 1b tokens em portugues iniciado com os pesos oficiais do modelo, o modelo não segue instrução então precisa fazer fine tuning.
| | Mistral Base PTBR | Mistral Base | Melhoria |
|------------------------------|-------------------|--------------|--... | {"language": ["pt"], "license": "apache-2.0", "datasets": ["nicholasKluge/Pt-Corpus"]} | JJhooww/Mistral-7B-v0.2-Base_ptbr | 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": []} | Grayx/unstable_76 | null | [
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# Model Card for Model ID
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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. -->
# flan-t5-small-yelp-text-classification
This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/googl... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "google/flan-t5-small", "model-index": [{"name": "flan-t5-small-yelp-text-classification", "results": []}]} | morturr/flan-t5-small-yelp-text-classification | null | [
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|
# flan-t5-small-yelp-text-classification
This model is a fine-tuned version of google/flan-t5-small on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
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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"]} | YolandiTheNinja/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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reinforcement-learning | transformers |
# TRL Model
This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
## Usage
To use this model for inference, first install the TR... | {"license": "apache-2.0", "tags": ["trl", "ppo", "transformers", "reinforcement-learning"]} | PranavBP525/phi-2-storygen-v1 | null | [
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|
# TRL Model
This is a TRL language model that has been fine-tuned with reinforcement learning to
guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
## Usage
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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": ["trl", "sft"]} | mjm765/PYStar_NER_comment_all_mistral_after_user_ignore | null | [
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#transformers #safetensors #mistral #text-generation #trl #sft #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | null | # Grok-1
This repository contains JAX example code for loading and running the Grok-1 open-weights model.
Make sure to download the checkpoint and place the `ckpt-0` directory in `checkpoints` - see [Downloading the weights](#downloading-the-weights)
Then, run
```shell
pip install -r requirements.txt
python run.py
... | {} | Abhay438/francia18.3.4 | null | [
"region:us"
] | null | 2024-04-11T15:15:15+00:00 | [] | [] | TAGS
#region-us
| # Grok-1
This repository contains JAX example code for loading and running the Grok-1 open-weights model.
Make sure to download the checkpoint and place the 'ckpt-0' directory in 'checkpoints' - see Downloading the weights
Then, run
to test the code.
The script loads the checkpoint and samples from the model on ... | [
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null | null |
this is lora https://civitai.com/models/300306?modelVersionId=337267
| {"license": "mit"} | jaxmetaverse/hologram_Laser_dress | null | [
"license:mit",
"region:us"
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#license-mit #region-us
|
this is lora 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. -->
# logs_100
This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "TheBloke/Mistral-7B-Instruct-v0.2-GPTQ", "model-index": [{"name": "logs_100", "results": []}]} | Jordano700/logs_100 | null | [
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#peft #safetensors #generated_from_trainer #base_model-TheBloke/Mistral-7B-Instruct-v0.2-GPTQ #license-apache-2.0 #region-us
| logs\_100
=========
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6145
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
Mo... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps:... | [
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text-generation | transformers | # LoftQ Initialization
| [Paper](https://arxiv.org/abs/2310.08659) | [Code](https://github.com/yxli2123/LoftQ) | [PEFT Example](https://github.com/huggingface/peft/tree/main/examples/loftq_finetuning) |
LoftQ (LoRA-fine-tuning-aware Quantization) provides a quantized backbone Q and LoRA adapters A and B, given a full... | {"language": ["en"], "license": "mit", "tags": ["quantization ", "lora"], "pipeline_tag": "text-generation"} | LoftQ/phi-2-4bit-64rank | null | [
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"region:us"
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| LoftQ Initialization
====================
| Paper | Code | PEFT Example |
LoftQ (LoRA-fine-tuning-aware Quantization) provides a quantized backbone Q and LoRA adapters A and B, given a full-precision pre-trained weight W.
This model, 'phi-2-4bit-64rank', is obtained from phi-2.
The backbone is under 'LoftQ/phi-2-... | [
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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": []} | unrented5443/dggzvsn | null | [
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"safetensors",
"stablelm",
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"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
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"1910.09700"
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#transformers #safetensors #stablelm #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/mistral-community/Mixtral-8x22B-v0.1
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/Mixt... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["moe"], "base_model": "mistral-community/Mixtral-8x22B-v0.1", "quantized_by": "mradermacher"} | mradermacher/Mixtral-8x22B-v0.1-i1-GGUF | null | [
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| 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 #moe #en #base_model-mistral-community/Mixtral-8x22B-v0.1 #license-apache-2.0 #endpoints_compatible #region-us \n"
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text-generation | transformers | # free-solar-0.3-exl2
Original model: [free-solar-slerp-v0.3](https://huggingface.co/freewheelin/free-solar-slerp-v0.3)
Model creator: [freewheelin](https://huggingface.co/freewheelin/)
# Quants
[4bpw h6 (main)](https://huggingface.co/cgus/free-solar-slerp-v0.3/tree/main)
[4.25bpw h6](https://huggingface.co/cgus/f... | {"language": ["ko"], "license": "mit", "tags": ["mergekit", "merge"], "model_name": "free-solar-slerp-v0.3", "base_model": ["freewheelin/free-solar-slerp-v0.3"], "quantized_by": "cgus", "model_creator": "freewheelin", "inference": false} | cgus/free-solar-slerp-v0.3-exl2 | null | [
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"base_model:freewheelin/free-solar-slerp-v0.3",
"license:mit",
"autotrain_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-11T15:26:31+00:00 | [] | [
"ko"
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#transformers #llama #text-generation #mergekit #merge #ko #base_model-freewheelin/free-solar-slerp-v0.3 #license-mit #autotrain_compatible #text-generation-inference #region-us
| # free-solar-0.3-exl2
Original model: free-solar-slerp-v0.3
Model creator: freewheelin
# Quants
4bpw h6 (main)
4.25bpw h6
4.65bpw h6
5bpw h6
6bpw h6
8bpw h8
# Quantization notes
Made with Exllamav2 0.0.15 with the default dataset.
This model has unusually long loading times, normal 11B models take abo... | [
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