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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 0.0001_withdpo_4iters_bs256_51005lr_iter_4
This model is a fine-tuned version of [ShenaoZ/0.0001_withdpo_4iters_bs256_511lr_iter... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "ShenaoZ/0.0001_withdpo_4iters_bs256_511lr_iter_3", "model-index": [{"name": "0.0001_withdpo_4iters_bs256_51005lr_iter_4", "results": []}]} | ShenaoZ/0.0001_withdpo_4iters_bs256_51005lr_iter_4 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"alignment-handbook",
"generated_from_trainer",
"trl",
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"dataset:original",
"base_model:ShenaoZ/0.0001_withdpo_4iters_bs256_511lr_iter_3",
"license:mit",
"autotrain_compatible",
"endpo... | null | 2024-05-02T19:13:21+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #alignment-handbook #generated_from_trainer #trl #dpo #conversational #dataset-updated #dataset-original #base_model-ShenaoZ/0.0001_withdpo_4iters_bs256_511lr_iter_3 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# 0.0001_withdpo_4iters_bs256_51005lr_iter_4
This model is a fine-tuned version of ShenaoZ/0.0001_withdpo_4iters_bs256_511lr_iter_3 on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More... | [
"# 0.0001_withdpo_4iters_bs256_51005lr_iter_4\n\nThis model is a fine-tuned version of ShenaoZ/0.0001_withdpo_4iters_bs256_511lr_iter_3 on the updated and the original datasets.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and e... | [
"TAGS\n#transformers #safetensors #mistral #text-generation #alignment-handbook #generated_from_trainer #trl #dpo #conversational #dataset-updated #dataset-original #base_model-ShenaoZ/0.0001_withdpo_4iters_bs256_511lr_iter_3 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #regio... | [
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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... | mejdi86/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-05-02T19:14:11+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
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
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"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add you... | [
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] |
text-classification | transformers | ERROR: type should be string, got "\nhttps://huggingface.co/SamLowe/roberta-base-go_emotions converted to ONNX to use with transformers.js\n\n---\n\n#### Overview\n\nModel trained from [roberta-base](https://huggingface.co/roberta-base) on the [go_emotions](https://huggingface.co/datasets/go_emotions) dataset for multi-label classification.\n\n##### ONNX version also available\n\nA version of this model in ONNX format (including an INT8 quantized ONNX version) is now available at [https://huggingface.co/SamLowe/roberta-base-go_emotions-onnx](https://huggingface.co/SamLowe/roberta-base-go_emotions-onnx). These are faster for inference, esp for smaller batch sizes, massively reduce the size of the dependencies required for inference, make inference of the model more multi-platform, and in the case of the quantized version reduce the model file/download size by 75% whilst retaining almost all the accuracy if you only need inference.\n\n#### Dataset used for the model\n\n[go_emotions](https://huggingface.co/datasets/go_emotions) is based on Reddit data and has 28 labels. It is a multi-label dataset where one or multiple labels may apply for any given input text, hence this model is a multi-label classification model with 28 'probability' float outputs for any given input text. Typically a threshold of 0.5 is applied to the probabilities for the prediction for each label.\n\n#### How the model was created\n\nThe model was trained using `AutoModelForSequenceClassification.from_pretrained` with `problem_type=\"multi_label_classification\"` for 3 epochs with a learning rate of 2e-5 and weight decay of 0.01.\n\n#### Inference\n\nThere are multiple ways to use this model in Huggingface Transformers. Possibly the simplest is using a pipeline:\n\n```python\nfrom transformers import pipeline\n\nclassifier = pipeline(task=\"text-classification\", model=\"SamLowe/roberta-base-go_emotions\", top_k=None)\n\nsentences = [\"I am not having a great day\"]\n\nmodel_outputs = classifier(sentences)\nprint(model_outputs[0])\n# produces a list of dicts for each of the labels\n```\n\n#### Evaluation / metrics\n\nEvaluation of the model is available at\n\n- https://github.com/samlowe/go_emotions-dataset/blob/main/eval-roberta-base-go_emotions.ipynb\n\n[](https://colab.research.google.com/github/samlowe/go_emotions-dataset/blob/main/eval-roberta-base-go_emotions.ipynb)\n\n##### Summary\n\nAs provided in the above notebook, evaluation of the multi-label output (of the 28 dim output via a threshold of 0.5 to binarize each) using the dataset test split gives:\n\n- Accuracy: 0.474\n- Precision: 0.575\n- Recall: 0.396\n- F1: 0.450\n\nBut the metrics are more meaningful when measured per label given the multi-label nature (each label is effectively an independent binary classification) and the fact that there is drastically different representations of the labels in the dataset.\n\nWith a threshold of 0.5 applied to binarize the model outputs, as per the above notebook, the metrics per label are:\n\n| | accuracy | precision | recall | f1 | mcc | support | threshold |\n| -------------- | -------- | --------- | ------ | ----- | ----- | ------- | --------- |\n| admiration | 0.946 | 0.725 | 0.675 | 0.699 | 0.670 | 504 | 0.5 |\n| amusement | 0.982 | 0.790 | 0.871 | 0.829 | 0.821 | 264 | 0.5 |\n| anger | 0.970 | 0.652 | 0.379 | 0.479 | 0.483 | 198 | 0.5 |\n| annoyance | 0.940 | 0.472 | 0.159 | 0.238 | 0.250 | 320 | 0.5 |\n| approval | 0.942 | 0.609 | 0.302 | 0.404 | 0.403 | 351 | 0.5 |\n| caring | 0.973 | 0.448 | 0.319 | 0.372 | 0.364 | 135 | 0.5 |\n| confusion | 0.972 | 0.500 | 0.431 | 0.463 | 0.450 | 153 | 0.5 |\n| curiosity | 0.950 | 0.537 | 0.356 | 0.428 | 0.412 | 284 | 0.5 |\n| desire | 0.987 | 0.630 | 0.410 | 0.496 | 0.502 | 83 | 0.5 |\n| disappointment | 0.974 | 0.625 | 0.199 | 0.302 | 0.343 | 151 | 0.5 |\n| disapproval | 0.950 | 0.494 | 0.307 | 0.379 | 0.365 | 267 | 0.5 |\n| disgust | 0.982 | 0.707 | 0.333 | 0.453 | 0.478 | 123 | 0.5 |\n| embarrassment | 0.994 | 0.750 | 0.243 | 0.367 | 0.425 | 37 | 0.5 |\n| excitement | 0.983 | 0.603 | 0.340 | 0.435 | 0.445 | 103 | 0.5 |\n| fear | 0.992 | 0.758 | 0.603 | 0.671 | 0.672 | 78 | 0.5 |\n| gratitude | 0.990 | 0.960 | 0.881 | 0.919 | 0.914 | 352 | 0.5 |\n| grief | 0.999 | 0.000 | 0.000 | 0.000 | 0.000 | 6 | 0.5 |\n| joy | 0.978 | 0.647 | 0.559 | 0.600 | 0.590 | 161 | 0.5 |\n| love | 0.982 | 0.773 | 0.832 | 0.802 | 0.793 | 238 | 0.5 |\n| nervousness | 0.996 | 0.600 | 0.130 | 0.214 | 0.278 | 23 | 0.5 |\n| optimism | 0.972 | 0.667 | 0.376 | 0.481 | 0.488 | 186 | 0.5 |\n| pride | 0.997 | 0.000 | 0.000 | 0.000 | 0.000 | 16 | 0.5 |\n| realization | 0.974 | 0.541 | 0.138 | 0.220 | 0.264 | 145 | 0.5 |\n| relief | 0.998 | 0.000 | 0.000 | 0.000 | 0.000 | 11 | 0.5 |\n| remorse | 0.991 | 0.553 | 0.750 | 0.636 | 0.640 | 56 | 0.5 |\n| sadness | 0.977 | 0.621 | 0.494 | 0.550 | 0.542 | 156 | 0.5 |\n| surprise | 0.981 | 0.750 | 0.404 | 0.525 | 0.542 | 141 | 0.5 |\n| neutral | 0.782 | 0.694 | 0.604 | 0.646 | 0.492 | 1787 | 0.5 |\n\nOptimizing the threshold per label for the one that gives the optimum F1 metrics gives slightly better metrics - sacrificing some precision for a greater gain in recall, hence to the benefit of F1 (how this was done is shown in the above notebook):\n\n| | accuracy | precision | recall | f1 | mcc | support | threshold |\n| -------------- | -------- | --------- | ------ | ----- | ----- | ------- | --------- |\n| admiration | 0.940 | 0.651 | 0.776 | 0.708 | 0.678 | 504 | 0.25 |\n| amusement | 0.982 | 0.781 | 0.890 | 0.832 | 0.825 | 264 | 0.45 |\n| anger | 0.959 | 0.454 | 0.601 | 0.517 | 0.502 | 198 | 0.15 |\n| annoyance | 0.864 | 0.243 | 0.619 | 0.349 | 0.328 | 320 | 0.10 |\n| approval | 0.926 | 0.432 | 0.442 | 0.437 | 0.397 | 351 | 0.30 |\n| caring | 0.972 | 0.426 | 0.385 | 0.405 | 0.391 | 135 | 0.40 |\n| confusion | 0.974 | 0.548 | 0.412 | 0.470 | 0.462 | 153 | 0.55 |\n| curiosity | 0.943 | 0.473 | 0.711 | 0.568 | 0.552 | 284 | 0.25 |\n| desire | 0.985 | 0.518 | 0.530 | 0.524 | 0.516 | 83 | 0.25 |\n| disappointment | 0.974 | 0.562 | 0.298 | 0.390 | 0.398 | 151 | 0.40 |\n| disapproval | 0.941 | 0.414 | 0.468 | 0.439 | 0.409 | 267 | 0.30 |\n| disgust | 0.978 | 0.523 | 0.463 | 0.491 | 0.481 | 123 | 0.20 |\n| embarrassment | 0.994 | 0.567 | 0.459 | 0.507 | 0.507 | 37 | 0.10 |\n| excitement | 0.981 | 0.500 | 0.417 | 0.455 | 0.447 | 103 | 0.35 |\n| fear | 0.991 | 0.712 | 0.667 | 0.689 | 0.685 | 78 | 0.40 |\n| gratitude | 0.990 | 0.957 | 0.889 | 0.922 | 0.917 | 352 | 0.45 |\n| grief | 0.999 | 0.333 | 0.333 | 0.333 | 0.333 | 6 | 0.05 |\n| joy | 0.978 | 0.623 | 0.646 | 0.634 | 0.623 | 161 | 0.40 |\n| love | 0.982 | 0.740 | 0.899 | 0.812 | 0.807 | 238 | 0.25 |\n| nervousness | 0.996 | 0.571 | 0.348 | 0.432 | 0.444 | 23 | 0.25 |\n| optimism | 0.971 | 0.580 | 0.565 | 0.572 | 0.557 | 186 | 0.20 |\n| pride | 0.998 | 0.875 | 0.438 | 0.583 | 0.618 | 16 | 0.10 |\n| realization | 0.961 | 0.270 | 0.262 | 0.266 | 0.246 | 145 | 0.15 |\n| relief | 0.992 | 0.152 | 0.636 | 0.246 | 0.309 | 11 | 0.05 |\n| remorse | 0.991 | 0.541 | 0.946 | 0.688 | 0.712 | 56 | 0.10 |\n| sadness | 0.977 | 0.599 | 0.583 | 0.591 | 0.579 | 156 | 0.40 |\n| surprise | 0.977 | 0.543 | 0.674 | 0.601 | 0.593 | 141 | 0.15 |\n| neutral | 0.758 | 0.598 | 0.810 | 0.688 | 0.513 | 1787 | 0.25 |\n\nThis improves the overall metrics:\n\n- Precision: 0.542\n- Recall: 0.577\n- F1: 0.541\n\nOr if calculated weighted by the relative size of the support of each label:\n\n- Precision: 0.572\n- Recall: 0.677\n- F1: 0.611\n\n#### Commentary on the dataset\n\nSome labels (E.g. gratitude) when considered independently perform very strongly with F1 exceeding 0.9, whilst others (E.g. relief) perform very poorly.\n\nThis is a challenging dataset. Labels such as relief do have much fewer examples in the training data (less than 100 out of the 40k+, and only 11 in the test split).\n\nBut there is also some ambiguity and/or labelling errors visible in the training data of go_emotions that is suspected to constrain the performance. Data cleaning on the dataset to reduce some of the mistakes, ambiguity, conflicts and duplication in the labelling would produce a higher performing model." | {"language": "en", "license": "mit", "tags": ["text-classification", "pytorch", "roberta", "emotions", "multi-class-classification", "multi-label-classification"], "datasets": ["go_emotions"], "widget": [{"text": "I am not having a great day."}]} | Cohee/roberta-base-go_emotions-onnx | null | [
"transformers",
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"roberta",
"text-classification",
"pytorch",
"emotions",
"multi-class-classification",
"multi-label-classification",
"en",
"dataset:go_emotions",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-05-02T19:15:51+00:00 | [] | [
"en"
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#transformers #onnx #roberta #text-classification #pytorch #emotions #multi-class-classification #multi-label-classification #en #dataset-go_emotions #license-mit #autotrain_compatible #endpoints_compatible #region-us
| URL converted to ONNX to use with URL
---
#### Overview
Model trained from roberta-base on the go\_emotions dataset for multi-label classification.
##### ONNX version also available
A version of this model in ONNX format (including an INT8 quantized ONNX version) is now available at URL These are faster for... | [
"#### Overview\n\n\nModel trained from roberta-base on the go\\_emotions dataset for multi-label classification.",
"##### ONNX version also available\n\n\nA version of this model in ONNX format (including an INT8 quantized ONNX version) is now available at URL These are faster for inference, esp for smaller batch... | [
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null | transformers |
# Uploaded model
- **Developed by:** Trappu
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/ma... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | Trappu/Picaro-lora-l3 | null | [
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"region:us"
] | null | 2024-05-02T19:17:07+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #text-generation-inference #unsloth #llama #trl #en #base_model-unsloth/llama-3-8b-bnb-4bit #license-apache-2.0 #endpoints_compatible #region-us
|
# Uploaded model
- Developed by: Trappu
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
"# Uploaded model\n\n- Developed by: Trappu\n- License: apache-2.0\n- Finetuned from model : unsloth/llama-3-8b-bnb-4bit\n\nThis llama model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
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text-generation | transformers |
## 4-bit GEMM AWQ Quantizations of ChatQA-1.5-8B
Using <a href="https://github.com/casper-hansen/AutoAWQ/">AutoAWQ</a> release <a href="https://github.com/casper-hansen/AutoAWQ/releases/tag/v0.2.4">v0.2.4</a> for quantization.
Original model: https://huggingface.co/nvidia/ChatQA-1.5-8B
## Prompt format
```
<|begi... | {"language": ["en"], "license": "llama3", "tags": ["nvidia", "chatqa-1.5", "chatqa", "llama-3", "pytorch"], "pipeline_tag": "text-generation", "quantized_by": "bartowski"} | bartowski/ChatQA-1.5-8B-AWQ | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"nvidia",
"chatqa-1.5",
"chatqa",
"llama-3",
"pytorch",
"conversational",
"en",
"license:llama3",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"region:us"
] | null | 2024-05-02T19:18:50+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #llama #text-generation #nvidia #chatqa-1.5 #chatqa #llama-3 #pytorch #conversational #en #license-llama3 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
|
## 4-bit GEMM AWQ Quantizations of ChatQA-1.5-8B
Using <a href="URL release <a href="URL for quantization.
Original model: URL
## Prompt format
## AWQ Parameters
- q_group_size: 128
- w_bit: 4
- zero_point: True
- version: GEMM
## How to run
From the AutoAWQ repo here
First install autoawq pypi package:... | [
"## 4-bit GEMM AWQ Quantizations of ChatQA-1.5-8B\n\nUsing <a href=\"URL release <a href=\"URL for quantization.\n\nOriginal model: URL",
"## Prompt format",
"## AWQ Parameters\n\n - q_group_size: 128\n - w_bit: 4\n - zero_point: True\n - version: GEMM",
"## How to run\n\nFrom the AutoAWQ repo here\n\nFirst ... | [
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reinforcement-learning | ml-agents |
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget**
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... | {"library_name": "ml-agents", "tags": ["SnowballTarget", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SnowballTarget"]} | Alvaroooooooo/ppo-SnowballTarget | null | [
"ml-agents",
"tensorboard",
"onnx",
"SnowballTarget",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SnowballTarget",
"region:us"
] | null | 2024-05-02T19:19:12+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #SnowballTarget #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SnowballTarget #region-us
|
# ppo Agent playing SnowballTarget
This is a trained model of a ppo agent playing SnowballTarget
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 tuto... | [
"# ppo Agent playing SnowballTarget\n This is a trained model of a ppo agent playing SnowballTarget\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *... | [
"TAGS\n#ml-agents #tensorboard #onnx #SnowballTarget #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SnowballTarget #region-us \n",
"# ppo Agent playing SnowballTarget\n This is a trained model of a ppo agent playing SnowballTarget\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agen... | [
39,
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null | transformers |
# Uploaded model
- **Developed by:** Chord-Llama
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unslo... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | Chord-Llama/Llama-3-chord-llama-chechpoint-5 | null | [
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# Uploaded model
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<img src="URL width="200"/>
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null | transformers | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/NousResearch/Meta-Llama-3-70B-Instruct
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher... | {"language": ["en"], "license": "other", "library_name": "transformers", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3"], "base_model": "NousResearch/Meta-Llama-3-70B-Instruct", "extra_gated_button_content": "Submit", "extra_gated_fields": {"Affiliation": "text", "By clicking Submit below I accept the terms... | mradermacher/Meta-Llama-3-70B-Instruct-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. ... | [] | [
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text-generation | transformers |
![image/png](https://cdn-uploads.huggingface.co/production/uploads/641b435ba... | {"language": ["en", "es"], "license": "apache-2.0", "datasets": ["NickyNicky/oasst2_orpo_mix_tokenizer_phi_3_v1"]} | NickyNicky/Phi-3-mini-4k-instruct_orpo_V2 | null | [
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!image/png
!image/png
!image/png
!image/png
## Metrics
## colab examples.
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reinforcement-learning | null |
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
| {"tags": ["Pixelcopter-PLE-v0", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-pixel18h", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pixelcopter-PLE-v0", "type": "Pixelcopter-PLE-v... | ahforoughi/Reinforce-pixel18h | null | [
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"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
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#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing Pixelcopter-PLE-v0
This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
| [
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text-classification | 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. -->
# llama3-qwantz-coherent
This model is a fine-tuned version of [unsloth/llama-3-8b-bnb-4bit](https://huggingface.co/unsloth/llama-... | {"license": "llama2", "library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "unsloth/llama-3-8b-bnb-4bit", "pipeline_tag": "text-classification", "model-index": [{"name": "llama3-qwantz-coherent", "results": []}]} | paul-stansifer/llama3-qwantz-coherent | null | [
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"generated_from_trainer",
"text-classification",
"base_model:unsloth/llama-3-8b-bnb-4bit",
"license:llama2",
"region:us"
] | null | 2024-05-02T19:23:45+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #generated_from_trainer #text-classification #base_model-unsloth/llama-3-8b-bnb-4bit #license-llama2 #region-us
| llama3-qwantz-coherent
======================
This model is a fine-tuned version of unsloth/llama-3-8b-bnb-4bit on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3295
* Accuracy: 0.8758
Model description
-----------------
More information needed
Intended uses & limitati... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\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: 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": []} | AstroMLab/astrogemma-7B | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | transformers |
This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
- Library: [More Information Needed]
- Docs: [More Information Needed] | {"tags": ["pytorch_model_hub_mixin", "model_hub_mixin"]} | UphamProjects/STT-Gated_TCN-12M | null | [
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#transformers #safetensors #pytorch_model_hub_mixin #model_hub_mixin #endpoints_compatible #region-us
|
This model has been pushed to the Hub using the PytorchModelHubMixin integration:
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mbart_extratranslations2
This model is a fine-tuned version of [NegarSH/mbart_extratranslations](https://huggingface.co/NegarSH/... | {"tags": ["generated_from_trainer"], "base_model": "NegarSH/mbart_extratranslations", "model-index": [{"name": "mbart_extratranslations2", "results": []}]} | NegarSH/mbart_extratranslations2 | null | [
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|
# mbart_extratranslations2
This model is a fine-tuned version of NegarSH/mbart_extratranslations on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training... | [
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text-to-image | diffusers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
... | {"library_name": "diffusers"} | rubbrband/ambienceSDXL_a1 | null | [
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## Model Details
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This is the model card of a diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
Atom-7B-Chat - bnb 8bits
- Model creator: https://huggingface.co/FlagAlpha/
- Original model: https://huggingface.co/FlagAlp... | {} | RichardErkhov/FlagAlpha_-_Atom-7B-Chat-8bits | null | [
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#transformers #safetensors #llama #text-generation #custom_code #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
Atom-7B-Chat - bnb 8bits
* Model creator: URL
* Original model: URL
Original model description:
---------------------------
developers: [URL
license: apache-2.0
language:
* zh
* en
pipeline\_tag: question-answering
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null | null | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
openchat-3.5-0106 - GGUF
- Model creator: https://huggingface.co/openchat/
- Original model: https://huggingface.co/openchat... | {} | RichardErkhov/openchat_-_openchat-3.5-0106-gguf | null | [
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#gguf #arxiv-2309.11235 #arxiv-2303.08774 #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
openchat-3.5-0106 - GGUF
* Model creator: URL
* Original model: URL
Name: openchat-3.5-0106.Q2\_K.gguf, Quant method: Q2\_K, Size: 2.53GB
Name: openchat-3.5-0106.IQ3\_XS.gguf, Quant method: IQ3\_XS, Size: 2.81GB
Name: openchat-3.5-0106.... | [
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-small-finetuned-wikiauto
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["wiki_auto"], "base_model": "google-t5/t5-small", "model-index": [{"name": "t5-small-finetuned-wikiauto", "results": []}]} | hiramochoavea/t5-small-finetuned-wikiauto | null | [
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| t5-small-finetuned-wikiauto
===========================
This model is a fine-tuned version of google-t5/t5-small on the wiki\_auto dataset.
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data... | [
"### 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: 1\n* mixed\\_prec... | [
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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": []} | ms6641/gpt2-imdb-pos-v2 | null | [
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|
# Model Card for Model ID
## Model Details
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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text-generation | null |
## Llamacpp imatrix Quantizations of Einstein-v6.1-Llama3-8B
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2777">b2777</a> for quantization.
Original model: https://huggingface.co/Weyaxi/Einstein-v6.1-Llama3-8B
All quants ... | {"language": ["en"], "license": "other", "tags": ["axolotl", "generated_from_trainer", "instruct", "finetune", "chatml", "gpt4", "synthetic data", "science", "physics", "chemistry", "biology", "math", "llama", "llama3"], "datasets": ["allenai/ai2_arc", "camel-ai/physics", "camel-ai/chemistry", "camel-ai/biology", "came... | bartowski/Einstein-v6.1-Llama3-8B-GGUF | null | [
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---------------------------------------------------------
Using <a href="URL release <a href="URL for quantization.
Original model: URL
All quants made using imatrix option with dataset provided by Kalomaze here
Prompt format
-------------
Download a f... | [] | [
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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?"}]}]} | Miyamowoto/autotrain-dbchy-3yaw5 | null | [
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#transformers #tensorboard #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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text-generation | transformers |
# Uploaded model
- **Developed by:** LeroyDyer
- **License:** apache-2.0
- **Finetuned from model :** LeroyDyer/Mixtral_AI_CyberTron_Ultra
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/unslot... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "LeroyDyer/Mixtral_AI_CyberTron_Ultra"} | LeroyDyer/Mixtral_AI_CyberLord | null | [
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|
# Uploaded model
- Developed by: LeroyDyer
- License: apache-2.0
- Finetuned from model : LeroyDyer/Mixtral_AI_CyberTron_Ultra
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
llama-7b - bnb 4bits
- Model creator: https://huggingface.co/huggyllama/
- Original model: https://huggingface.co/huggyllama... | {} | RichardErkhov/huggyllama_-_llama-7b-4bits | null | [
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#transformers #safetensors #llama #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
llama-7b - bnb 4bits
- Model creator: URL
- Original model: URL
Original model description:
---
license: other
---
This contains the weights for the LLaMA-7b model. This model is under a non-commercial license (see the LICENSE file).
You ... | [] | [
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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": []} | vishruthnath/deepseek_ft_1024 | null | [
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|
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# llama2-poison-20p-0502
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-... | {"license": "llama2", "library_name": "peft", "tags": ["alignment-handbook", "trl", "sft", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrachat_200k"], "base_model": "meta-llama/Llama-2-7b-hf", "model-index": [{"name": "llama2-poison-20p-0502", "results": []}]} | Jackie999/llama2-poison-20p-0502 | null | [
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| llama2-poison-20p-0502
======================
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the HuggingFaceH4/ultrachat\_200k dataset.
It achieves the following results on the evaluation set:
* Loss: nan
Model description
-----------------
More information needed
Intended uses & limitation... | [
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null | null | Collection of LoRA files for my finetune. First, there was DPO on adamo1139/rawrr_v2-2_stage1 for 1 epoch. Then, SFT training on adamo1139/AEZAKMI_v3-7 for 0.5 epochs. Then, ORPO training on adamo1139/toxic-dpo-natural-v5 for 1 epoch.\
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reinforcement-learning | null |
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
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#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
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# Reinforce Agent playing Pixelcopter-PLE-v0
This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
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null | peft |
# CHAST
This model is a fine-tuned version of [lmsys/vicuna-13b-v1.5-16k](https://huggingface.co/lmsys/vicuna-13b-v1.5-16k).
## Model description
Computes Covert Harms and Social Threats (CHAST) metrics for conversational data.
### Training hyperparameters
The following hyperparameters were used during training:... | {"license": "apache-2.0", "library_name": "peft", "tags": ["lora"], "base_model": "lmsys/vicuna-13b-v1.5-16k", "model-index": [{"name": "CHAST", "results": []}]} | SocialCompUW/CHAST | null | [
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#peft #safetensors #lora #base_model-lmsys/vicuna-13b-v1.5-16k #license-apache-2.0 #region-us
|
# CHAST
This model is a fine-tuned version of lmsys/vicuna-13b-v1.5-16k.
## Model description
Computes Covert Harms and Social Threats (CHAST) metrics for conversational data.
### Training hyperparameters
The following hyperparameters were used during training:
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 0.0001_withdpo_3iters_bs256_531lr_iter_1
This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggi... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "HuggingFaceH4/mistral-7b-sft-beta", "model-index": [{"name": "0.0001_withdpo_3iters_bs256_531lr_iter_1", "results": []}]} | ShenaoZ/0.0001_withdpo_3iters_bs256_531lr_iter_1 | null | [
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|
# 0.0001_withdpo_3iters_bs256_531lr_iter_1
This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the HuggingFaceH4/ultrafeedback_binarized dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
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text-generation | mlx |
# mlx-community/Llama3-ChatQA-1.5-8B-4bit
This model was converted to MLX format from [`mlx-community/Llama3-ChatQA-1.5-8B`]() using mlx-lm version **0.12.0**.
Model added by [Prince Canuma](https://twitter.com/Prince_Canuma).
Refer to the [original model card](https://huggingface.co/nvidia/Llama3-ChatQA-1.5-8B) for... | {"language": ["en"], "license": "other", "tags": ["facebook", "nvidia", "meta", "pytorch", "llama", "llama-3", "mlx"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE"} | mlx-community/Llama3-ChatQA-1.5-8B-4bit | null | [
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|
# mlx-community/Llama3-ChatQA-1.5-8B-4bit
This model was converted to MLX format from ['mlx-community/Llama3-ChatQA-1.5-8B']() using mlx-lm version 0.12.0.
Model added by Prince Canuma.
Refer to the original model card for more details on the model.
## Use with mlx
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text-generation | mlx |
# mlx-community/Llama3-ChatQA-1.5-8B-8bit
This model was converted to MLX format from [`mlx-community/Llama3-ChatQA-1.5-8B`]() using mlx-lm version **0.12.0**.
Model added by [Prince Canuma](https://twitter.com/Prince_Canuma).
Refer to the [original model card](https://huggingface.co/nvidia/Llama3-ChatQA-1.5-8B) for... | {"language": ["en"], "license": "other", "tags": ["facebook", "nvidia", "meta", "pytorch", "llama", "llama-3", "mlx"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE"} | mlx-community/Llama3-ChatQA-1.5-8B-8bit | null | [
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# mlx-community/Llama3-ChatQA-1.5-8B-8bit
This model was converted to MLX format from ['mlx-community/Llama3-ChatQA-1.5-8B']() using mlx-lm version 0.12.0.
Model added by Prince Canuma.
Refer to the original model card for more details on the model.
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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": []} | vaughnhatfield/my-test-pipeline | null | [
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
llama-7b - bnb 8bits
- Model creator: https://huggingface.co/huggyllama/
- Original model: https://huggingface.co/huggyllama... | {} | RichardErkhov/huggyllama_-_llama-7b-8bits | null | [
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| Quantization made by Richard Erkhov.
Github
Discord
Request more models
llama-7b - bnb 8bits
- Model creator: URL
- Original model: URL
Original model description:
---
license: other
---
This contains the weights for the LLaMA-7b model. This model is under a non-commercial license (see the LICENSE file).
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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": []} | jamesohe/casaudit2-4bit-p01-adapter | null | [
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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. -->
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text-generation | transformers |
# Model Card for Model ID
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## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | abc88767/model45 | null | [
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null | null | # Rommel (Gundam Build Divers)
**Trained on**: fluffyrock-megares-tsnr-vpred-e159 (7ab6d6f252)
**Resolution**: 512x512
**Data set**: 45 images, mainly from the television series
**Trigger tag**: rommel
**Suggested tags**: anthro, white body, mustelid, hat, topwear, bottomless
| {} | HatefulSable/rommel | null | [
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#region-us
| # Rommel (Gundam Build Divers)
Trained on: fluffyrock-megares-tsnr-vpred-e159 (7ab6d6f252)
Resolution: 512x512
Data set: 45 images, mainly from the television series
Trigger tag: rommel
Suggested tags: anthro, white body, mustelid, hat, topwear, bottomless
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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"]} | eddyejembi/PoemLib_FineTuned | null | [
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|
# Model Card for Model ID
## Model Details
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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-chat-hf"} | magnifi/llama-cls-ner-mt-chat-v21-9_epoch_10 | null | [
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text-generation | transformers | 1.5 epochs of QingyiSi/Alpaca-CoT over athirdpath/Llama-3-15b-Instruct-GLUED
Are you sure this is your final answer?
 | {"license": "llama3"} | athirdpath/Llama-3-15b-Instruct-CoT | null | [
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#transformers #safetensors #llama #text-generation #conversational #license-llama3 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| 1.5 epochs of QingyiSi/Alpaca-CoT over athirdpath/Llama-3-15b-Instruct-GLUED
Are you sure this is your final answer?
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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-case-ner
This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-b... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "google-bert/bert-base-cased", "model-index": [{"name": "bert-base-case-ner", "results": []}]} | raulgdp/bert-base-case-ner | null | [
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#transformers #tensorboard #safetensors #bert #token-classification #generated_from_trainer #base_model-google-bert/bert-base-cased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| bert-base-case-ner
==================
This model is a fine-tuned version of google-bert/bert-base-cased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1741
* Precision: 0.7713
* Recall: 0.8081
* F1: 0.7893
* Accuracy: 0.9675
Model description
-----------------
More inf... | [
"### 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 |
# 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": []} | xp0tat0/farmer_8 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
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null | null | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
llama-7b - GGUF
- Model creator: https://huggingface.co/huggyllama/
- Original model: https://huggingface.co/huggyllama/llam... | {} | RichardErkhov/huggyllama_-_llama-7b-gguf | null | [
"gguf",
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#gguf #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
llama-7b - GGUF
* Model creator: URL
* Original model: URL
Name: llama-7b.Q2\_K.gguf, Quant method: Q2\_K, Size: 2.36GB
Name: llama-7b.IQ3\_XS.gguf, Quant method: IQ3\_XS, Size: 2.6GB
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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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width... | {"license": "llama2", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "codellama/CodeLlama-7b-hf", "model-index": [{"name": "stage1", "results": []}]} | aphamm/stage1 | null | [
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"base_model:codellama/CodeLlama-7b-hf",
"license:llama2",
"region:us"
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#peft #generated_from_trainer #base_model-codellama/CodeLlama-7b-hf #license-llama2 #region-us
|
<img src="URL alt="Visualize in Weights & Biases" width="200" height="32"/>
# stage1
This model is a fine-tuned version of codellama/CodeLlama-7b-hf on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More i... | [
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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. -->
# fiqa-bot-v1
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-L... | {"license": "other", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "meta-llama/Meta-Llama-3-8B-Instruct", "model-index": [{"name": "fiqa-bot-v1", "results": []}]} | Sorour/fiqa-bot-v1 | null | [
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#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-meta-llama/Meta-Llama-3-8B-Instruct #license-other #region-us
|
# fiqa-bot-v1
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the generator dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyp... | [
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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": []} | obh07/Meta-llama-3-8B-Instruct-GPTQ-4Bit | null | [
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#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
|
# Model Card for Model ID
## Model Details
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 0.0001_withdpo_3iters_bs256_511lr_iter_1
This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggi... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "HuggingFaceH4/mistral-7b-sft-beta", "model-index": [{"name": "0.0001_withdpo_3iters_bs256_511lr_iter_1", "results": []}]} | ShenaoZ/0.0001_withdpo_3iters_bs256_511lr_iter_1 | null | [
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|
# 0.0001_withdpo_3iters_bs256_511lr_iter_1
This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the HuggingFaceH4/ultrafeedback_binarized dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
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More info... | [
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null | transformers |
# Uploaded model
- **Developed by:** CodeTriad
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-instruct-v0.2-bnb-4bit
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/u... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-instruct-v0.2-bnb-4bit"} | CodeTriad/mistral_instruct_7754_epoch2_dpo | null | [
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|
# Uploaded model
- Developed by: CodeTriad
- 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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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-7b-instruct-v0.2-bnb-4bit_Finetuned_usloth_dataset_size_52_epochs_10_Hyperparameter
This model is a fine-tuned version o... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "unsloth", "generated_from_trainer"], "metrics": ["accuracy", "bleu", "sacrebleu", "rouge"], "base_model": "unsloth/mistral-7b-instruct-v0.2-bnb-4bit", "model-index": [{"name": "mistral-7b-instruct-v0.2-bnb-4bit_Finetuned_usloth_dataset_size_52_ep... | vdavidr/mistral-7b-instruct-v0.2-bnb-4bit_Finetuned_usloth_dataset_size_52_epochs_10_Hyperparameter | null | [
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"base_model:unsloth/mistral-7b-instruct-v0.2-bnb-4bit",
"license:apache-2.0",
"region:us"
] | null | 2024-05-02T20:12:51+00:00 | [] | [] | TAGS
#peft #safetensors #trl #sft #unsloth #generated_from_trainer #base_model-unsloth/mistral-7b-instruct-v0.2-bnb-4bit #license-apache-2.0 #region-us
| mistral-7b-instruct-v0.2-bnb-4bit\_Finetuned\_usloth\_dataset\_size\_52\_epochs\_10\_Hyperparameter
===================================================================================================
This model is a fine-tuned version of unsloth/mistral-7b-instruct-v0.2-bnb-4bit on the None dataset.
It achieves the f... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1.1795554702080496e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 3407\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam with betas=(0.9,0.... | [
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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?"}]}]} | abhishek/autotrain-llama3-70b-orpo-v1 | null | [
"transformers",
"tensorboard",
"safetensors",
"llama",
"text-generation",
"autotrain",
"text-generation-inference",
"peft",
"conversational",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-05-02T20:13:41+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #llama #text-generation #autotrain #text-generation-inference #peft #conversational #license-other #autotrain_compatible #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
# Usage
| [
"# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.",
"# Usage"
] | [
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
CodeLlama-7b-hf - bnb 4bits
- Model creator: https://huggingface.co/codellama/
- Original model: https://huggingface.co/code... | {} | RichardErkhov/codellama_-_CodeLlama-7b-hf-4bits | null | [
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"text-generation",
"arxiv:2308.12950",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"region:us"
] | null | 2024-05-02T20:15:16+00:00 | [
"2308.12950"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #arxiv-2308.12950 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
CodeLlama-7b-hf - bnb 4bits
* Model creator: URL
* Original model: URL
Original model description:
---------------------------
language:
* code
pipeline\_tag: text-generation
tags:
* llama-2
license: llama2
---
Code Llama
====... | [] | [
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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-7B-Instruct-v0.2-finetune-SWE_70_30
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://h... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "Mistral-7B-Instruct-v0.2-finetune-SWE_70_30", "results": []}]} | JuanjoLopez19/Mistral-7B-Instruct-v0.2-finetune-SWE_70_30 | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"license:apache-2.0",
"region:us"
] | null | 2024-05-02T20:20:25+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mistralai/Mistral-7B-Instruct-v0.2 #license-apache-2.0 #region-us
| Mistral-7B-Instruct-v0.2-finetune-SWE\_70\_30
=============================================
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1810
Model description
-----------------
More information... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\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: constant\n* num\\_epochs: 5\n* mixed\\_pre... | [
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text-to-image | diffusers |
# AutoTrain SDXL LoRA DreamBooth - kpal002/Dreambooth-SDXL
<Gallery />
## Model description
These are kpal002/Dreambooth-SDXL LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using [DreamBooth](https://dreambooth.github.io/).
LoRA for the text encoder was enabled: ... | {"license": "openrail++", "tags": ["autotrain", "stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "lora", "template:sd-lora"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "A portrait in a distinctive expressive style characterized by vivid color use, ... | kpal002/exactly-ai-finetuned-diffusion-model | null | [
"diffusers",
"autotrain",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"text-to-image",
"lora",
"template:sd-lora",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"region:us"
] | null | 2024-05-02T20:20:27+00:00 | [] | [] | TAGS
#diffusers #autotrain #stable-diffusion-xl #stable-diffusion-xl-diffusers #text-to-image #lora #template-sd-lora #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-openrail++ #region-us
|
# AutoTrain SDXL LoRA DreamBooth - kpal002/Dreambooth-SDXL
<Gallery />
## Model description
These are kpal002/Dreambooth-SDXL LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using DreamBooth.
LoRA for the text encoder was enabled: False.
Special VAE used for trai... | [
"# AutoTrain SDXL LoRA DreamBooth - kpal002/Dreambooth-SDXL\n\n<Gallery />",
"## Model description\n\nThese are kpal002/Dreambooth-SDXL LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.\n\nThe weights were trained using DreamBooth.\n\nLoRA for the text encoder was enabled: False.\n\nSpecial VAE... | [
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"# AutoTrain SDXL LoRA DreamBooth - kpal002/Dreambooth-SDXL\n\n<Gallery />",
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text-generation | null |
## Model Details
We introduce Llama3-ChatQA-1.5, which excels at conversational question answering (QA) and retrieval-augumented generation (RAG). Llama3-ChatQA-1.5 is built using the training recipe from [ChatQA (1.0)](https://arxiv.org/abs/2401.10225), and it is built on top of [Llama-3 base model](https://huggingf... | {"language": ["en"], "license": "llama3", "tags": ["nvidia", "chatqa-1.5", "chatqa", "llama-3", "pytorch"], "pipeline_tag": "text-generation"} | LoneStriker/Llama3-ChatQA-1.5-8B-GGUF | null | [
"gguf",
"nvidia",
"chatqa-1.5",
"chatqa",
"llama-3",
"pytorch",
"text-generation",
"en",
"arxiv:2401.10225",
"license:llama3",
"region:us"
] | null | 2024-05-02T20:20:45+00:00 | [
"2401.10225"
] | [
"en"
] | TAGS
#gguf #nvidia #chatqa-1.5 #chatqa #llama-3 #pytorch #text-generation #en #arxiv-2401.10225 #license-llama3 #region-us
| Model Details
-------------
We introduce Llama3-ChatQA-1.5, which excels at conversational question answering (QA) and retrieval-augumented generation (RAG). Llama3-ChatQA-1.5 is built using the training recipe from ChatQA (1.0), and it is built on top of Llama-3 base model. Additionally, we incorporate more conversa... | [
"### take the whole document as context\n\n\nThis can be applied to the scenario where the whole document can be fitted into the model, so that there is no need to run retrieval over the document.",
"### run retrieval to get top-n chunks as context\n\n\nThis can be applied to the scenario when the document is ver... | [
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
CodeLlama-7b-hf - bnb 8bits
- Model creator: https://huggingface.co/codellama/
- Original model: https://huggingface.co/code... | {} | RichardErkhov/codellama_-_CodeLlama-7b-hf-8bits | null | [
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"text-generation",
"arxiv:2308.12950",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"8-bit",
"region:us"
] | null | 2024-05-02T20:21:13+00:00 | [
"2308.12950"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #arxiv-2308.12950 #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
CodeLlama-7b-hf - bnb 8bits
* Model creator: URL
* Original model: URL
Original model description:
---------------------------
language:
* code
pipeline\_tag: text-generation
tags:
* llama-2
license: llama2
---
Code Llama
====... | [] | [
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] |
null | transformers | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/Undi95/Llama3-Unholy-8B-OAS
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/Llama3-Unhol... | {"language": ["en"], "license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["not-for-all-audiences", "nsfw"], "base_model": "Undi95/Llama3-Unholy-8B-OAS", "quantized_by": "mradermacher"} | mradermacher/Llama3-Unholy-8B-OAS-i1-GGUF | null | [
"transformers",
"gguf",
"not-for-all-audiences",
"nsfw",
"en",
"base_model:Undi95/Llama3-Unholy-8B-OAS",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | null | 2024-05-02T20:21:18+00:00 | [] | [
"en"
] | TAGS
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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. ... | [] | [
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] |
text-generation | null |
## Exllama v2 Quantizations of dolphin-2.9-llama3-8b-1m
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.20">turboderp's ExLlamaV2 v0.0.20</a> for quantization.
<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
Each branc... | {"license": "other", "tags": ["generated_from_trainer", "axolotl"], "datasets": ["cognitivecomputations/Dolphin-2.9", "teknium/OpenHermes-2.5", "m-a-p/CodeFeedback-Filtered-Instruction", "cognitivecomputations/dolphin-coder", "cognitivecomputations/samantha-data", "HuggingFaceH4/ultrachat_200k", "microsoft/orca-math-wo... | bartowski/dolphin-2.9-llama3-8b-1m-exl2 | null | [
"generated_from_trainer",
"axolotl",
"text-generation",
"dataset:cognitivecomputations/Dolphin-2.9",
"dataset:teknium/OpenHermes-2.5",
"dataset:m-a-p/CodeFeedback-Filtered-Instruction",
"dataset:cognitivecomputations/dolphin-coder",
"dataset:cognitivecomputations/samantha-data",
"dataset:HuggingFace... | null | 2024-05-02T20:22:10+00:00 | [] | [] | TAGS
#generated_from_trainer #axolotl #text-generation #dataset-cognitivecomputations/Dolphin-2.9 #dataset-teknium/OpenHermes-2.5 #dataset-m-a-p/CodeFeedback-Filtered-Instruction #dataset-cognitivecomputations/dolphin-coder #dataset-cognitivecomputations/samantha-data #dataset-HuggingFaceH4/ultrachat_200k #dataset-micr... | Exllama v2 Quantizations of dolphin-2.9-llama3-8b-1m
----------------------------------------------------
Using <a href="URL ExLlamaV2 v0.0.20 for quantization.
**The "main" branch only contains the URL, download one of the other branches for the model (see below)**
Each branch contains an individual bits per wei... | [] | [
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187
] | [
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text-to-image | diffusers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
... | {"library_name": "diffusers"} | rubbrband/ivisionIllustration_ivision10 | null | [
"diffusers",
"safetensors",
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This is the model card of a diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | null | # [MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.2-GGUF](https://huggingface.co/MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.2-GGUF)
- Model creator: [MaziyarPanahi](https://huggingface.co/MaziyarPanahi)
- Original model: [MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.2](https://huggingface.co/MaziyarPanahi/Llama-3-70B-Instruct-D... | {"tags": ["quantized", "2-bit", "3-bit", "4-bit", "5-bit", "6-bit", "8-bit", "GGUF", "text-generation", "llama", "llama-3", "text-generation"], "model_name": "Llama-3-70B-Instruct-DPO-v0.2-GGUF", "base_model": "MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.2", "inference": false, "model_creator": "MaziyarPanahi", "pipeline... | MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.2-GGUF | null | [
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| # MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.2-GGUF
- Model creator: MaziyarPanahi
- Original model: MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.2
## Description
MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.2-GGUF contains GGUF format model files for MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.2.
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reinforcement-learning | null |
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
| {"tags": ["Pixelcopter-PLE-v0", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-Pixelcopter2", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pixelcopter-PLE-v0", "type": "Pixelcopter-P... | rwr20/Reinforce-Pixelcopter2 | null | [
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#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing Pixelcopter-PLE-v0
This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results_tou
This model is a fine-tuned version of [meta-llama/Llama-2-13b-chat-hf](https://huggingface.co/meta-llama/Llama-2-13b... | {"license": "llama2", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "meta-llama/Llama-2-13b-chat-hf", "model-index": [{"name": "results_tou", "results": []}]} | Destructo565/results_tou | null | [
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|
# results_tou
This model is a fine-tuned version of meta-llama/Llama-2-13b-chat-hf on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
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reinforcement-learning | null |
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
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|
# Reinforce Agent playing Pixelcopter-PLE-v0
This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
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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": []} | azhara001/donut-base-demo-new-v2-0.0003_Adam_938 | 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": []} | shallow6414/q5kiicb | null | [
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
OpenHermes-2.5-Mistral-7B - bnb 4bits
- Model creator: https://huggingface.co/teknium/
- Original model: https://huggingface... | {} | RichardErkhov/teknium_-_OpenHermes-2.5-Mistral-7B-4bits | null | [
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#transformers #safetensors #mistral #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
OpenHermes-2.5-Mistral-7B - bnb 4bits
- Model creator: URL
- Original model: URL
Original model description:
---
base_model: mistralai/Mistral-7B-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": []} | shallow6414/z3ua8pc | 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": []} | lunarsylph/stablecell_v61 | null | [
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null | diffusers | This model is a collection of files from https://huggingface.co/huchenlei/animal_openpose/tree/main
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null | transformers |
# Uploaded model
- **Developed by:** Arara10
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-bnb-4bit
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-bnb-4bit"} | Arara10/wolf-coder-mistral-adptr | null | [
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# Uploaded model
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- License: apache-2.0
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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?"}]}]} | Miyamowoto/aoiChatbot-wBert-uncased-v1 | null | [
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# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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text-generation | transformers |
## Model Details
We introduce Llama3-ChatQA-1.5, which excels at conversational question answering (QA) and retrieval-augumented generation (RAG). Llama3-ChatQA-1.5 is built using the training recipe from [ChatQA (1.0)](https://arxiv.org/abs/2401.10225), and it is built on top of [Llama-3 base model](https://huggingf... | {"language": ["en"], "license": "llama3", "tags": ["nvidia", "chatqa-1.5", "chatqa", "llama-3", "pytorch"], "pipeline_tag": "text-generation"} | LoneStriker/Llama3-ChatQA-1.5-8B-3.0bpw-h6-exl2 | null | [
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| Model Details
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- 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": []} | golf2248/2322ova | null | [
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
OpenHermes-2.5-Mistral-7B - bnb 8bits
- Model creator: https://huggingface.co/teknium/
- Original model: https://huggingface... | {} | RichardErkhov/teknium_-_OpenHermes-2.5-Mistral-7B-8bits | null | [
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| Quantization made by Richard Erkhov.
Github
Discord
Request more models
OpenHermes-2.5-Mistral-7B - bnb 8bits
- Model creator: URL
- Original model: URL
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---
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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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feature-extraction | transformers |
# Model Card for Model ID
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text-generation | transformers |
## Model Details
We introduce Llama3-ChatQA-1.5, which excels at conversational question answering (QA) and retrieval-augumented generation (RAG). Llama3-ChatQA-1.5 is built using the training recipe from [ChatQA (1.0)](https://arxiv.org/abs/2401.10225), and it is built on top of [Llama-3 base model](https://huggingf... | {"language": ["en"], "license": "llama3", "tags": ["nvidia", "chatqa-1.5", "chatqa", "llama-3", "pytorch"], "pipeline_tag": "text-generation"} | LoneStriker/Llama3-ChatQA-1.5-8B-4.0bpw-h6-exl2 | null | [
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feature-extraction | transformers |
# Model Card for Model ID
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### Model Description
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text-to-image | diffusers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
... | {"library_name": "diffusers"} | rubbrband/remasterizexl_v10 | null | [
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## Model Details
### Model Description
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | golf2248/nd5xxwk | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
## Model Details
We introduce Llama3-ChatQA-1.5, which excels at conversational question answering (QA) and retrieval-augumented generation (RAG). Llama3-ChatQA-1.5 is built using the training recipe from [ChatQA (1.0)](https://arxiv.org/abs/2401.10225), and it is built on top of [Llama-3 base model](https://huggingf... | {"language": ["en"], "license": "llama3", "tags": ["nvidia", "chatqa-1.5", "chatqa", "llama-3", "pytorch"], "pipeline_tag": "text-generation"} | LoneStriker/Llama3-ChatQA-1.5-8B-5.0bpw-h6-exl2 | null | [
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| Model Details
-------------
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feature-extraction | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | lyghter/2ch-wt-24-01-01-27480-3849-mel-512-pool-016e7-1x032-1-1 | null | [
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"1910.09700"
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my-wav2vec2-base
This model was trained from scratch on an unknown dataset.
## Model description
More information needed
## I... | {"tags": ["generated_from_trainer"], "model-index": [{"name": "my-wav2vec2-base", "results": []}]} | mariasawalha/my-wav2vec2-base | null | [
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|
# my-wav2vec2-base
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
### Training hyperparameters
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text-generation | transformers |
## Model Details
We introduce Llama3-ChatQA-1.5, which excels at conversational question answering (QA) and retrieval-augumented generation (RAG). Llama3-ChatQA-1.5 is built using the training recipe from [ChatQA (1.0)](https://arxiv.org/abs/2401.10225), and it is built on top of [Llama-3 base model](https://huggingf... | {"language": ["en"], "license": "llama3", "tags": ["nvidia", "chatqa-1.5", "chatqa", "llama-3", "pytorch"], "pipeline_tag": "text-generation"} | LoneStriker/Llama3-ChatQA-1.5-8B-6.0bpw-h6-exl2 | null | [
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| Model Details
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sentence-similarity | sentence-transformers |
# seregadgl101/baii_v6_4ep
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model becom... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | seregadgl101/baii_v6_4ep | null | [
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#sentence-transformers #safetensors #xlm-roberta #feature-extraction #sentence-similarity #endpoints_compatible #region-us
|
# seregadgl101/baii_v6_4ep
This is a sentence-transformers model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | shallow6414/ptnkxf4 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="emmermarcell/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additiona... | {"tags": ["FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-noSlippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4-no_slippery", "type": ... | emmermarcell/q-FrozenLake-v1-4x4-noSlippery | null | [
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#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
## Usage
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null | null | <!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hfhfix -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/NousResearch/Meta-Llama-3-70B
| {} | mradermacher/Meta-Llama-3-70B-i1-GGUF | null | [
"gguf",
"region:us"
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#gguf #region-us
|
weighted/imatrix quants of URL
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# RoBERTa_BART_hybrid_V1
This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) o... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["arrow"], "base_model": "facebook/bart-large", "model-index": [{"name": "RoBERTa_BART_hybrid_V1", "results": []}]} | MikaSie/even_testen | null | [
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"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-05-02T20:49:53+00:00 | [] | [] | TAGS
#transformers #safetensors #bart #text2text-generation #generated_from_trainer #dataset-arrow #base_model-facebook/bart-large #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| RoBERTa\_BART\_hybrid\_V1
=========================
This model is a fine-tuned version of facebook/bart-large on the arrow dataset.
It achieves the following results on the evaluation set:
* Loss: 2.0946
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: 16\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\\_ratio... | [
"TAGS\n#transformers #safetensors #bart #text2text-generation #generated_from_trainer #dataset-arrow #base_model-facebook/bart-large #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* le... | [
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text-generation | transformers |
## Model Details
We introduce Llama3-ChatQA-1.5, which excels at conversational question answering (QA) and retrieval-augumented generation (RAG). Llama3-ChatQA-1.5 is built using the training recipe from [ChatQA (1.0)](https://arxiv.org/abs/2401.10225), and it is built on top of [Llama-3 base model](https://huggingf... | {"language": ["en"], "license": "llama3", "tags": ["nvidia", "chatqa-1.5", "chatqa", "llama-3", "pytorch"], "pipeline_tag": "text-generation"} | LoneStriker/Llama3-ChatQA-1.5-8B-8.0bpw-h8-exl2 | null | [
"transformers",
"pytorch",
"llama",
"text-generation",
"nvidia",
"chatqa-1.5",
"chatqa",
"llama-3",
"en",
"arxiv:2401.10225",
"license:llama3",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"8-bit",
"region:us"
] | null | 2024-05-02T20:50:15+00:00 | [
"2401.10225"
] | [
"en"
] | TAGS
#transformers #pytorch #llama #text-generation #nvidia #chatqa-1.5 #chatqa #llama-3 #en #arxiv-2401.10225 #license-llama3 #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us
| Model Details
-------------
We introduce Llama3-ChatQA-1.5, which excels at conversational question answering (QA) and retrieval-augumented generation (RAG). Llama3-ChatQA-1.5 is built using the training recipe from ChatQA (1.0), and it is built on top of Llama-3 base model. Additionally, we incorporate more conversa... | [
"### take the whole document as context\n\n\nThis can be applied to the scenario where the whole document can be fitted into the model, so that there is no need to run retrieval over the document.",
"### run retrieval to get top-n chunks as context\n\n\nThis can be applied to the scenario when the document is ver... | [
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reinforcement-learning | ml-agents |
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget**
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... | {"library_name": "ml-agents", "tags": ["SnowballTarget", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SnowballTarget"]} | haytamelouarrat/ppo-SnowballTarget | null | [
"ml-agents",
"tensorboard",
"onnx",
"SnowballTarget",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SnowballTarget",
"region:us"
] | null | 2024-05-02T20:51:28+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #SnowballTarget #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SnowballTarget #region-us
|
# ppo Agent playing SnowballTarget
This is a trained model of a ppo agent playing SnowballTarget
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 tuto... | [
"# ppo Agent playing SnowballTarget\n This is a trained model of a ppo agent playing SnowballTarget\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *... | [
"TAGS\n#ml-agents #tensorboard #onnx #SnowballTarget #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SnowballTarget #region-us \n",
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"TAGS\n#ml-agents #tensorboard #onnx #SnowballTarget #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SnowballTarget #region-us \n# ppo Agent playing SnowballTarget\n This is a trained model of a ppo agent playing SnowballTarget\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n ... |
reinforcement-learning | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="emmermarcell/q-learning-Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slipper... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-learning-Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value":... | emmermarcell/q-learning-Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-05-02T20:51:34+00:00 | [] | [] | TAGS
#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
## Usage
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] |
fill-mask | transformers |
## Environmental Impact (CODE CARBON DEFAULT)
| Metric | Value |
|--------------------------|---------------------------------|
| Duration (in seconds) | [More Information Needed] |
| Emissions (Co2eq in kg) | [More Information Needed] |
| CPU power (W) | [N... | {"language": "en", "tags": ["fill-mask"]} | damgomz/BERTrand_bs16_lr5_MLM | null | [
"transformers",
"safetensors",
"albert",
"fill-mask",
"en",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-05-02T20:52:53+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #albert #fill-mask #en #autotrain_compatible #endpoints_compatible #region-us
| Environmental Impact (CODE CARBON DEFAULT)
------------------------------------------
Environmental Impact (for one core)
-----------------------------------
Note
----
2 May 2024
My Config
---------
Training and Testing steps
--------------------------
Epoch: 0.0, Train Loss: 14.743229, Test Loss: 13.097... | [] | [
"TAGS\n#transformers #safetensors #albert #fill-mask #en #autotrain_compatible #endpoints_compatible #region-us \n"
] | [
29
] | [
"TAGS\n#transformers #safetensors #albert #fill-mask #en #autotrain_compatible #endpoints_compatible #region-us \n"
] |
null | null |
# CosmicbunEinstein-7B
CosmicbunEinstein-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
* [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct)
* [mlabonne/OrpoLlama-3-8B](https://huggingface.co/m... | {"license": "cc-by-nc-4.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"], "base_model": ["NousResearch/Meta-Llama-3-8B-Instruct", "mlabonne/OrpoLlama-3-8B"]} | automerger/CosmicbunEinstein-7B | null | [
"merge",
"mergekit",
"lazymergekit",
"automerger",
"base_model:NousResearch/Meta-Llama-3-8B-Instruct",
"base_model:mlabonne/OrpoLlama-3-8B",
"license:cc-by-nc-4.0",
"region:us"
] | null | 2024-05-02T20:52:59+00:00 | [] | [] | TAGS
#merge #mergekit #lazymergekit #automerger #base_model-NousResearch/Meta-Llama-3-8B-Instruct #base_model-mlabonne/OrpoLlama-3-8B #license-cc-by-nc-4.0 #region-us
|
# CosmicbunEinstein-7B
CosmicbunEinstein-7B is an automated merge created by Maxime Labonne using the following configuration.
* NousResearch/Meta-Llama-3-8B-Instruct
* mlabonne/OrpoLlama-3-8B
## Configuration
## Usage
| [
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text-generation | transformers |
# ⚡ExLlamaV2 quant of : [Lumimaid 0.1](https://huggingface.co/NeverSleep/Llama-3-Lumimaid-8B-v0.1)
➡️ **Exl2 version** : [0.0.20](https://github.com/turboderp/exllamav2/releases/tag/v0.0.20)<br/>
➡️ **Cal. dataset** : Default.<br/>
📄 <a href="https://huggingface.co/Meggido/Llama-3-Lumimaid-8B-v0.1-6.5bpw-h8-exl2/reso... | {"license": "cc-by-nc-4.0", "tags": ["not-for-all-audiences", "nsfw"]} | Meggido/Llama-3-Lumimaid-8B-v0.1-6.5bpw-h8-exl2 | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"not-for-all-audiences",
"nsfw",
"conversational",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-05-02T20:53:02+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #not-for-all-audiences #nsfw #conversational #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# ExLlamaV2 quant of : Lumimaid 0.1
️ Exl2 version : 0.0.20<br/>
️ Cal. dataset : Default.<br/>
<a href="URL download>URL</a> file.
## Lumimaid 0.1
<center><div style="width: 100%;">
<img src="URL style="display: block; margin: auto;">
</div></center>
This model uses the Llama3 prompting format
Llama3 trained... | [
"# ExLlamaV2 quant of : Lumimaid 0.1\n️ Exl2 version : 0.0.20<br/>\n️ Cal. dataset : Default.<br/>\n <a href=\"URL download>URL</a> file.",
"## Lumimaid 0.1\n\n<center><div style=\"width: 100%;\">\n <img src=\"URL style=\"display: block; margin: auto;\">\n</div></center>\n\nThis model uses the Llama3 prompting... | [
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null | null | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
OpenHermes-2.5-Mistral-7B - GGUF
- Model creator: https://huggingface.co/teknium/
- Original model: https://huggingface.co/t... | {} | RichardErkhov/teknium_-_OpenHermes-2.5-Mistral-7B-gguf | null | [
"gguf",
"region:us"
] | null | 2024-05-02T20:54:56+00:00 | [] | [] | TAGS
#gguf #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
OpenHermes-2.5-Mistral-7B - GGUF
* Model creator: URL
* Original model: URL
Name: OpenHermes-2.5-Mistral-7B.Q2\_K.gguf, Quant method: Q2\_K, Size: 2.53GB
Name: OpenHermes-2.5-Mistral-7B.IQ3\_XS.gguf, Quant method: IQ3\_XS, Size: 2.81GB
... | [
"### Chat about programming with a superintelligence:\n\n\n!image/png",
"### Get a gourmet meal recipe:\n\n\n!image/png",
"### Talk about the nature of Hermes' consciousness:\n\n\n!image/png",
"### Chat with Edward Elric from Fullmetal Alchemist:\n\n\n!image/png\n\n\nBenchmark Results\n-----------------\n\n\n... | [
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fill-mask | transformers |
## Environmental Impact (CODE CARBON DEFAULT)
| Metric | Value |
|--------------------------|---------------------------------|
| Duration (in seconds) | [More Information Needed] |
| Emissions (Co2eq in kg) | [More Information Needed] |
| CPU power (W) | [N... | {"language": "en", "tags": ["fill-mask"]} | damgomz/BERTrand_bs32_lr5_MLM | null | [
"transformers",
"safetensors",
"albert",
"fill-mask",
"en",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-05-02T20:56:28+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #albert #fill-mask #en #autotrain_compatible #endpoints_compatible #region-us
| Environmental Impact (CODE CARBON DEFAULT)
------------------------------------------
Environmental Impact (for one core)
-----------------------------------
Note
----
2 May 2024
My Config
---------
Training and Testing steps
--------------------------
Epoch: 0.0, Train Loss: 14.582730, Test Loss: 13.090... | [] | [
"TAGS\n#transformers #safetensors #albert #fill-mask #en #autotrain_compatible #endpoints_compatible #region-us \n"
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29
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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": []} | taaha3244/taahaOrpoLlama-3-8B | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-05-02T20:56:34+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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