richarderkhov/luckychao_-_tinyalpaca-1.1b-gguf overview

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    "summary": "This model checkpoint is the TinyLlama-1.1B fine-tuned on alpaca dataset.",
    "quick_links": [],
    "benchmark_table_html": "",
    "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\nTinyAlpaca-1.1B - GGUF\n- Model creator: https://huggingface.co/luckychao/\n- Original model: https://huggingface.co/luckychao/TinyAlpaca-1.1B/\n\n\n| Name | Quant method | Size |\n| ---- | ---- | ---- |\n| [TinyAlpaca-1.1B.Q2_K.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q2_K.gguf) | Q2_K | 0.4GB |\n| [TinyAlpaca-1.1B.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.IQ3_XS.gguf) | IQ3_XS | 0.44GB |\n| [TinyAlpaca-1.1B.IQ3_S.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.IQ3_S.gguf) | IQ3_S | 0.47GB |\n| [TinyAlpaca-1.1B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q3_K_S.gguf) | Q3_K_S | 0.47GB |\n| [TinyAlpaca-1.1B.IQ3_M.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.IQ3_M.gguf) | IQ3_M | 0.48GB |\n| [TinyAlpaca-1.1B.Q3_K.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q3_K.gguf) | Q3_K | 0.51GB |\n| [TinyAlpaca-1.1B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q3_K_M.gguf) | Q3_K_M | 0.51GB |\n| [TinyAlpaca-1.1B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q3_K_L.gguf) | Q3_K_L | 0.55GB |\n| [TinyAlpaca-1.1B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.IQ4_XS.gguf) | IQ4_XS | 0.57GB |\n| [TinyAlpaca-1.1B.Q4_0.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q4_0.gguf) | Q4_0 | 0.59GB |\n| [TinyAlpaca-1.1B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.IQ4_NL.gguf) | IQ4_NL | 0.6GB |\n| [TinyAlpaca-1.1B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q4_K_S.gguf) | Q4_K_S | 0.6GB |\n| [TinyAlpaca-1.1B.Q4_K.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q4_K.gguf) | Q4_K | 0.62GB |\n| [TinyAlpaca-1.1B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q4_K_M.gguf) | Q4_K_M | 0.62GB |\n| [TinyAlpaca-1.1B.Q4_1.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q4_1.gguf) | Q4_1 | 0.65GB |\n| [TinyAlpaca-1.1B.Q5_0.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q5_0.gguf) | Q5_0 | 0.71GB |\n| [TinyAlpaca-1.1B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q5_K_S.gguf) | Q5_K_S | 0.71GB |\n| [TinyAlpaca-1.1B.Q5_K.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q5_K.gguf) | Q5_K | 0.73GB |\n| [TinyAlpaca-1.1B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q5_K_M.gguf) | Q5_K_M | 0.73GB |\n| [TinyAlpaca-1.1B.Q5_1.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q5_1.gguf) | Q5_1 | 0.77GB |\n| [TinyAlpaca-1.1B.Q6_K.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q6_K.gguf) | Q6_K | 0.84GB |\n| [TinyAlpaca-1.1B.Q8_0.gguf](https://huggingface.co/RichardErkhov/luckychao_-_TinyAlpaca-1.1B-gguf/blob/main/TinyAlpaca-1.1B.Q8_0.gguf) | Q8_0 | 1.09GB |\n\n\n\n\nOriginal model description:\n---\nlanguage:\n- en\ndatasets:\n- tatsu-lab/alpaca\n---\n# Model Card for Model ID\n\nThis model checkpoint is the TinyLlama-1.1B fine-tuned on [alpaca dataset](https://huggingface.co/datasets/tatsu-lab/alpaca).\n\n## Model Details\n\n### Model Sources \n\n<!-- Provide the basic links for the model. -->\n\n- **Repository:** https://github.com/jzhang38/TinyLlama\n- **Paper:** [https://arxiv.org/abs/2404.02406]\n\n## Uses\n\n\nThe use of this model should comply with the restrictions from [TinyLlama-1.1b](https://github.com/jzhang38/TinyLlama) and \n[Stanford Alpaca](https://github.com/tatsu-lab/stanford_alpaca).\n\n## How to Get Started with the Model\n\nUse the code below to get started with the model.\n\n```\n# Load model directly\nfrom transformers import AutoTokenizer, AutoModelForCausalLM\n\ntokenizer = AutoTokenizer.from_pretrained(\"luckychao/TinyAlpaca-1.1B\")\nmodel = AutoModelForCausalLM.from_pretrained(\"luckychao/TinyAlpaca-1.1B\")\n\n```\n\n## Training Details\n\n### Training Data\n\nWe use the [alpaca dataset](https://huggingface.co/datasets/tatsu-lab/alpaca), which is created by researchers from Stanford University.\n\n### Training Procedure\n\nWe follow the same training procedure and mostly same hyper-parameters to fine-tune the original Alpaca model on Llama. The procedure can be found in [stanford_alpaca project](https://huggingface.co/datasets/tatsu-lab/alpaca).\n\n#### Training Hyperparameters\n```\n--num_train_epochs 3 \\\n--per_device_train_batch_size 2 \\\n--per_device_eval_batch_size 2 \\\n--gradient_accumulation_steps 4 \\\n--evaluation_strategy \"no\" \\\n--save_strategy \"steps\" \\\n--save_steps 1000 \\\n--save_total_limit 1 \\\n--learning_rate 2e-5 \\\n--weight_decay 0. \\\n--warmup_ratio 0.03 \\\n--lr_scheduler_type \"cosine\" \\\n--logging_steps 1 \\\n--bf16 True \\\n--fsdp \"full_shard auto_wrap\" \\\n--fsdp_transformer_layer_cls_to_wrap 'LlamaDecoderLayer' \\\n--model_max_length 2048 \n\n```\n\n\n## Citation \n\nThe model is mostly developed for the paper below. Please cite it if you find the repository helpful.\n\n**BibTeX:**\n```\n@article{hao2024exploring,\n  title={Exploring Backdoor Vulnerabilities of Chat Models},\n  author={Hao, Yunzhuo and Yang, Wenkai and Lin, Yankai},\n  journal={arXiv preprint arXiv:2404.02406},\n  year={2024}\n}\n```\n\n\n\n\n\n\n",
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  "tags": [
    "gguf",
    "arxiv:2404.02406",
    "endpoints_compatible",
    "region:us"
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  "last_modified": "2024-07-03T03:16:19.000Z",
  "created_at": "2024-07-03T03:09:07.000Z",
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