giprime_-_OOM-SOLAR-10.7B_02-gguf – AI Model by RichardErkhov | AlphaNeural AI

You can deploy this model and start earning money today!

RichardErkhov/
giprime_-_OOM-SOLAR-10.7B_02-gguf

like

0

endpoints_compatible

Views

No views yet

Quantization made by Richard Erkhov.

Request more models

OOM-SOLAR-10.7B_02 - GGUF

Model creator: https://huggingface.co/giprime/
Original model: https://huggingface.co/giprime/OOM-SOLAR-10.7B_02/

Name	Quant method	Size
OOM-SOLAR-10.7B_02.Q2_K.gguf	Q2_K	3.79GB
OOM-SOLAR-10.7B_02.IQ3_XS.gguf	IQ3_XS	4.21GB
OOM-SOLAR-10.7B_02.IQ3_S.gguf	IQ3_S	4.44GB
OOM-SOLAR-10.7B_02.Q3_K_S.gguf	Q3_K_S	4.41GB
OOM-SOLAR-10.7B_02.IQ3_M.gguf	IQ3_M	4.58GB
OOM-SOLAR-10.7B_02.Q3_K.gguf	Q3_K	4.91GB
OOM-SOLAR-10.7B_02.Q3_K_M.gguf	Q3_K_M	4.91GB
OOM-SOLAR-10.7B_02.Q3_K_L.gguf	Q3_K_L	5.33GB
OOM-SOLAR-10.7B_02.IQ4_XS.gguf	IQ4_XS	5.5GB
OOM-SOLAR-10.7B_02.Q4_0.gguf	Q4_0	5.73GB
OOM-SOLAR-10.7B_02.IQ4_NL.gguf	IQ4_NL	5.8GB
OOM-SOLAR-10.7B_02.Q4_K_S.gguf	Q4_K_S	5.78GB
OOM-SOLAR-10.7B_02.Q4_K.gguf	Q4_K	6.1GB
OOM-SOLAR-10.7B_02.Q4_K_M.gguf	Q4_K_M	6.1GB
OOM-SOLAR-10.7B_02.Q4_1.gguf	Q4_1	6.35GB
OOM-SOLAR-10.7B_02.Q5_0.gguf	Q5_0	6.97GB
OOM-SOLAR-10.7B_02.Q5_K_S.gguf	Q5_K_S	6.97GB
OOM-SOLAR-10.7B_02.Q5_K.gguf	Q5_K	7.16GB
OOM-SOLAR-10.7B_02.Q5_K_M.gguf	Q5_K_M	7.16GB
OOM-SOLAR-10.7B_02.Q5_1.gguf	Q5_1	7.59GB
OOM-SOLAR-10.7B_02.Q6_K.gguf	Q6_K	8.29GB
OOM-SOLAR-10.7B_02.Q8_0.gguf	Q8_0	10.74GB

Original model description:

license: apache-2.0 language:

en
ko library_name: transformers

Model Architecture

OOM-SOLAR-10.7B_02 is an language model that uses an optimized transformer architecture based on upstage/SOLAR-10.7B-v1.0.

Model description

Based on "beomi/OPEN-SOLAR-KO-10.7B"

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 2
eval_batch_size: 8
seed: 24
gradient_accumulation_steps: 1
total_train_batch_size:
num_epochs: 1.0

Training results

Framework versions

Transformers 4.37.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2