richarderkhov/mlfoundations_-_tabula-8b-gguf overview

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    "summary": "You can load the model with transformers via `` from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained(\"mlfoundations/tabula-8b\") model = AutoModelForCausalLM.from_pretrained(\"mlfoundations/tabula-8b\") `` For more information on how to prepare data and run inference (including a demo notebook for performing inference on your data), see the examples in rtfm. # License and Terms of Use TabuLa-8B is fine-tuned from the Llama-3 8B model. As a result, we release it under the Llama 3 license, and by using the model you agree to abide by the Llama 3 Community License Agreement and the Llama 3 Acceptable Use Policy.",
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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\ntabula-8b - GGUF\n- Model creator: https://huggingface.co/mlfoundations/\n- Original model: https://huggingface.co/mlfoundations/tabula-8b/\n\n\n| Name | Quant method | Size |\n| ---- | ---- | ---- |\n| [tabula-8b.Q2_K.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q2_K.gguf) | Q2_K | 2.96GB |\n| [tabula-8b.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.IQ3_XS.gguf) | IQ3_XS | 3.28GB |\n| [tabula-8b.IQ3_S.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.IQ3_S.gguf) | IQ3_S | 3.43GB |\n| [tabula-8b.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q3_K_S.gguf) | Q3_K_S | 3.41GB |\n| [tabula-8b.IQ3_M.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.IQ3_M.gguf) | IQ3_M | 3.52GB |\n| [tabula-8b.Q3_K.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q3_K.gguf) | Q3_K | 3.74GB |\n| [tabula-8b.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q3_K_M.gguf) | Q3_K_M | 3.74GB |\n| [tabula-8b.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q3_K_L.gguf) | Q3_K_L | 4.03GB |\n| [tabula-8b.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.IQ4_XS.gguf) | IQ4_XS | 4.18GB |\n| [tabula-8b.Q4_0.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q4_0.gguf) | Q4_0 | 4.34GB |\n| [tabula-8b.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.IQ4_NL.gguf) | IQ4_NL | 4.38GB |\n| [tabula-8b.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q4_K_S.gguf) | Q4_K_S | 4.37GB |\n| [tabula-8b.Q4_K.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q4_K.gguf) | Q4_K | 4.58GB |\n| [tabula-8b.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q4_K_M.gguf) | Q4_K_M | 4.58GB |\n| [tabula-8b.Q4_1.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q4_1.gguf) | Q4_1 | 4.78GB |\n| [tabula-8b.Q5_0.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q5_0.gguf) | Q5_0 | 5.21GB |\n| [tabula-8b.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q5_K_S.gguf) | Q5_K_S | 5.21GB |\n| [tabula-8b.Q5_K.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q5_K.gguf) | Q5_K | 5.34GB |\n| [tabula-8b.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q5_K_M.gguf) | Q5_K_M | 5.34GB |\n| [tabula-8b.Q5_1.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q5_1.gguf) | Q5_1 | 5.65GB |\n| [tabula-8b.Q6_K.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q6_K.gguf) | Q6_K | 6.14GB |\n| [tabula-8b.Q8_0.gguf](https://huggingface.co/RichardErkhov/mlfoundations_-_tabula-8b-gguf/blob/main/tabula-8b.Q8_0.gguf) | Q8_0 | 7.95GB |\n\n\n\n\nOriginal model description:\n---\nlicense: llama3\ndatasets:\n- jpgard/t4-full\nlanguage:\n- en\n---\n\nThis repository contains the TabuLa-8B (Tabular Llama-8B) model. \nTabuLa-8B is a foundation model for prediction (classification and binned regression) on tabular data.\n\nTabuLa-8B is described in the paper [\"Large Scale Transfer Learning for Tabular Data via Language Modeling.\"](https://arxiv.org/abs/2406.12031)\n\nFor more details on the model, see the paper, which includes a Model Card detailing the model architecture, training, and evaluation.\nTabuLa-8B was trained with [rtfm](https://github.com/mlfoundations/rtfm), \nusing the [T4 dataset](https://huggingface.co/datasets/mlfoundations/t4-full).\n\nTabuLa-8B is built with Meta Llama 3.\n\n# Usage and Examples\n\nYou can load the model with `transformers` via\n```\nfrom transformers import AutoTokenizer, AutoModelForCausalLM\n\ntokenizer = AutoTokenizer.from_pretrained(\"mlfoundations/tabula-8b\")\nmodel = AutoModelForCausalLM.from_pretrained(\"mlfoundations/tabula-8b\")\n```\n\nFor more information on how to prepare data and run inference (including a demo notebook for performing inference on your data), see the examples in [rtfm](https://github.com/mlfoundations/rtfm).\n\n# License and Terms of Use\n\nTabuLa-8B is fine-tuned from the Llama-3 8B model. \nAs a result, we release it under the [Llama 3 license](https://llama.meta.com/llama3/license/), \nand by using the model you agree to abide by the [Llama 3 Community License Agreement](https://llama.meta.com/llama3/license/) \nand the Llama 3 [Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).\n\n\n",
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  "tags": [
    "gguf",
    "arxiv:2406.12031",
    "endpoints_compatible",
    "region:us"
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  "last_modified": "2024-08-21T23:06:18.000Z",
  "created_at": "2024-08-21T21:29:48.000Z",
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