Downloads · 30 days
306
3% of all-time downloads
mlfoundations_-_tabula-8b-gguf
RichardErkhov/mlfoundations_-_tabula-8b-gguf
mlfoundations_-_tabula-8b-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
All-time downloads
9.3K
Public
Repo size
92.9 GB
Likes
1
Public
Repo makeup
Click a slice to open those files.
.gguf108 GB · 100%
At a glance
- Access
- Public
- Created
- Aug 21, 2024
- Updated
- Aug 21, 2024
- SHA
- 66f8ef2a
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
tabula-8b - GGUF
- Model creator: https://huggingface.co/mlfoundations/
- Original model: https://huggingface.co/mlfoundations/tabula-8b/
| Name | Quant method | Size |
|---|---|---|
| tabula-8b.Q2_K.gguf | Q2_K | 2.96GB |
| tabula-8b.IQ3_XS.gguf | IQ3_XS | 3.28GB |
| tabula-8b.IQ3_S.gguf | IQ3_S | 3.43GB |
| tabula-8b.Q3_K_S.gguf | Q3_K_S | 3.41GB |
| tabula-8b.IQ3_M.gguf | IQ3_M | 3.52GB |
| tabula-8b.Q3_K.gguf | Q3_K | 3.74GB |
| tabula-8b.Q3_K_M.gguf | Q3_K_M | 3.74GB |
| tabula-8b.Q3_K_L.gguf | Q3_K_L | 4.03GB |
| tabula-8b.IQ4_XS.gguf | IQ4_XS | 4.18GB |
| tabula-8b.Q4_0.gguf | Q4_0 | 4.34GB |
| tabula-8b.IQ4_NL.gguf | IQ4_NL | 4.38GB |
| tabula-8b.Q4_K_S.gguf | Q4_K_S | 4.37GB |
| tabula-8b.Q4_K.gguf | Q4_K | 4.58GB |
| tabula-8b.Q4_K_M.gguf | Q4_K_M | 4.58GB |
| tabula-8b.Q4_1.gguf | Q4_1 | 4.78GB |
| tabula-8b.Q5_0.gguf | Q5_0 | 5.21GB |
| tabula-8b.Q5_K_S.gguf | Q5_K_S | 5.21GB |
| tabula-8b.Q5_K.gguf | Q5_K | 5.34GB |
| tabula-8b.Q5_K_M.gguf | Q5_K_M | 5.34GB |
| tabula-8b.Q5_1.gguf | Q5_1 | 5.65GB |
| tabula-8b.Q6_K.gguf | Q6_K | 6.14GB |
| tabula-8b.Q8_0.gguf | Q8_0 | 7.95GB |
Original model description:
license: llama3 datasets:
- jpgard/t4-full language:
- en
This repository contains the TabuLa-8B (Tabular Llama-8B) model. TabuLa-8B is a foundation model for prediction (classification and binned regression) on tabular data.
TabuLa-8B is described in the paper "Large Scale Transfer Learning for Tabular Data via Language Modeling."
For more details on the model, see the paper, which includes a Model Card detailing the model architecture, training, and evaluation. TabuLa-8B was trained with rtfm, using the T4 dataset.
TabuLa-8B is built with Meta Llama 3.
Usage and Examples
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.
- Created
- Aug 21, 2024
- Updated
- Aug 21, 2024