richarderkhov/zahrapakzad_-_my_humorous_llm-model-gguf overview

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    "summary": "This model is a fine-tuned version of distilbert/distilgpt2 on the \"Reddit-clean-jokes\" dataset taken from the following link:  https://github.com/amoudgl/short-jokes-dataset/blob/master/data/reddit-cleanjokes.csv. It achieves the following results on the evaluation set:",
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    "readme_markdown": "Quantization made by Richard Erkhov.\n\n[Github](https://github.com/RichardErkhov)\n\n[Discord](https://discord.gg/pvy7H8DZMG)\n\n[Request more models](https://github.com/RichardErkhov/quant_request)\n\n\nmy_humorous_llm-model - GGUF\n- Model creator: https://huggingface.co/ZahraPakzad/\n- Original model: https://huggingface.co/ZahraPakzad/my_humorous_llm-model/\n\n\n| Name | Quant method | Size |\n| ---- | ---- | ---- |\n| [my_humorous_llm-model.Q2_K.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q2_K.gguf) | Q2_K | 0.06GB |\n| [my_humorous_llm-model.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.IQ3_XS.gguf) | IQ3_XS | 0.07GB |\n| [my_humorous_llm-model.IQ3_S.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.IQ3_S.gguf) | IQ3_S | 0.07GB |\n| [my_humorous_llm-model.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q3_K_S.gguf) | Q3_K_S | 0.07GB |\n| [my_humorous_llm-model.IQ3_M.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.IQ3_M.gguf) | IQ3_M | 0.07GB |\n| [my_humorous_llm-model.Q3_K.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q3_K.gguf) | Q3_K | 0.07GB |\n| [my_humorous_llm-model.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q3_K_M.gguf) | Q3_K_M | 0.07GB |\n| [my_humorous_llm-model.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q3_K_L.gguf) | Q3_K_L | 0.07GB |\n| [my_humorous_llm-model.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.IQ4_XS.gguf) | IQ4_XS | 0.07GB |\n| [my_humorous_llm-model.Q4_0.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q4_0.gguf) | Q4_0 | 0.08GB |\n| [my_humorous_llm-model.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.IQ4_NL.gguf) | IQ4_NL | 0.08GB |\n| [my_humorous_llm-model.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q4_K_S.gguf) | Q4_K_S | 0.08GB |\n| [my_humorous_llm-model.Q4_K.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q4_K.gguf) | Q4_K | 0.08GB |\n| [my_humorous_llm-model.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q4_K_M.gguf) | Q4_K_M | 0.08GB |\n| [my_humorous_llm-model.Q4_1.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q4_1.gguf) | Q4_1 | 0.08GB |\n| [my_humorous_llm-model.Q5_0.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q5_0.gguf) | Q5_0 | 0.09GB |\n| [my_humorous_llm-model.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q5_K_S.gguf) | Q5_K_S | 0.09GB |\n| [my_humorous_llm-model.Q5_K.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q5_K.gguf) | Q5_K | 0.09GB |\n| [my_humorous_llm-model.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q5_K_M.gguf) | Q5_K_M | 0.09GB |\n| [my_humorous_llm-model.Q5_1.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q5_1.gguf) | Q5_1 | 0.09GB |\n| [my_humorous_llm-model.Q6_K.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q6_K.gguf) | Q6_K | 0.1GB |\n| [my_humorous_llm-model.Q8_0.gguf](https://huggingface.co/RichardErkhov/ZahraPakzad_-_my_humorous_llm-model-gguf/blob/main/my_humorous_llm-model.Q8_0.gguf) | Q8_0 | 0.12GB |\n\n\n\n\nOriginal model description:\n---\nlibrary_name: transformers\nlicense: apache-2.0\nbase_model: distilbert/distilgpt2\ntags:\n- generated_from_trainer\nmodel-index:\n- name: my_humorous_llm-model\n  results: []\nlanguage:\n- en\nmetrics:\n- perplexity\n---\n\n<!-- This model card has been generated automatically according to the information the Trainer had access to. You\nshould probably proofread and complete it, then remove this comment. -->\n\n# my_humorous_llm-model\n\nThis model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co/distilbert/distilgpt2) on the \"Reddit-clean-jokes\" dataset taken from the following link:  https://github.com/amoudgl/short-jokes-dataset/blob/master/data/reddit-cleanjokes.csv.\nIt achieves the following results on the evaluation set:\n- Loss: 1.9830\n\n## Model description\n\nMore information needed\n\n## Intended uses & limitations\n\nMore information needed\n\n## Training and evaluation data\n\nMore information needed\n\n## Training procedure\n\n### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 8\n- eval_batch_size: 8\n- seed: 42\n- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments\n- lr_scheduler_type: linear\n- num_epochs: 3.0\n\n### Training results\n\n| Training Loss | Epoch | Step | Validation Loss |\n|:-------------:|:-----:|:----:|:---------------:|\n| No log        | 1.0   | 117  | 2.1182          |\n| No log        | 2.0   | 234  | 2.0096          |\n| No log        | 3.0   | 351  | 1.9830          |\n\n\n### Framework versions\n\n- Transformers 4.46.2\n- Pytorch 2.5.1+cu121\n- Datasets 3.1.0\n- Tokenizers 0.20.3\n\n",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "endpoints_compatible",
    "region:us"
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  "last_modified": "2025-02-12T00:16:52.000Z",
  "created_at": "2025-02-12T00:00:21.000Z",
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  "author": "RichardErkhov",
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