etri-xainlp_-_SOLAR-10.7B-merge-dpo_v1-gguf – AI Model by RichardErkhov | AlphaNeural AI

You can deploy this model and start earning money today!

RichardErkhov/
etri-xainlp_-_SOLAR-10.7B-merge-dpo_v1-gguf

like

0

endpoints_compatible

Views

No views yet

Quantization made by Richard Erkhov.

Request more models

SOLAR-10.7B-merge-dpo_v1 - GGUF

Model creator: https://huggingface.co/etri-xainlp/
Original model: https://huggingface.co/etri-xainlp/SOLAR-10.7B-merge-dpo_v1/

Name	Quant method	Size
SOLAR-10.7B-merge-dpo_v1.Q2_K.gguf	Q2_K	3.73GB
SOLAR-10.7B-merge-dpo_v1.IQ3_XS.gguf	IQ3_XS	4.14GB
SOLAR-10.7B-merge-dpo_v1.IQ3_S.gguf	IQ3_S	4.37GB
SOLAR-10.7B-merge-dpo_v1.Q3_K_S.gguf	Q3_K_S	4.34GB
SOLAR-10.7B-merge-dpo_v1.IQ3_M.gguf	IQ3_M	4.51GB
SOLAR-10.7B-merge-dpo_v1.Q3_K.gguf	Q3_K	4.84GB
SOLAR-10.7B-merge-dpo_v1.Q3_K_M.gguf	Q3_K_M	4.84GB
SOLAR-10.7B-merge-dpo_v1.Q3_K_L.gguf	Q3_K_L	5.26GB
SOLAR-10.7B-merge-dpo_v1.IQ4_XS.gguf	IQ4_XS	5.43GB
SOLAR-10.7B-merge-dpo_v1.Q4_0.gguf	Q4_0	5.66GB
SOLAR-10.7B-merge-dpo_v1.IQ4_NL.gguf	IQ4_NL	5.72GB
SOLAR-10.7B-merge-dpo_v1.Q4_K_S.gguf	Q4_K_S	5.7GB
SOLAR-10.7B-merge-dpo_v1.Q4_K.gguf	Q4_K	6.02GB
SOLAR-10.7B-merge-dpo_v1.Q4_K_M.gguf	Q4_K_M	6.02GB
SOLAR-10.7B-merge-dpo_v1.Q4_1.gguf	Q4_1	6.27GB
SOLAR-10.7B-merge-dpo_v1.Q5_0.gguf	Q5_0	6.89GB
SOLAR-10.7B-merge-dpo_v1.Q5_K_S.gguf	Q5_K_S	6.89GB
SOLAR-10.7B-merge-dpo_v1.Q5_K.gguf	Q5_K	7.08GB
SOLAR-10.7B-merge-dpo_v1.Q5_K_M.gguf	Q5_K_M	7.08GB
SOLAR-10.7B-merge-dpo_v1.Q5_1.gguf	Q5_1	7.51GB
SOLAR-10.7B-merge-dpo_v1.Q6_K.gguf	Q6_K	8.2GB
SOLAR-10.7B-merge-dpo_v1.Q8_0.gguf	Q8_0	10.62GB

Original model description:

license: cc-by-nc-4.0 tags:

merge

etri-xainlp/SOLAR-10.7B-merge-dpo_v1

Model Details

Model Developers ETRI xainlp team

Input text only.

Output text only.

Model Architecture

We used MergeKit to merge Model heavytail/kullm-solar into Model etri-xainlp/SOLAR-10.7B-merge-dpo as the base.

Base Model etri-xainlp/SOLAR-10.7B-merge-dpo

Merge Model davidkim205/komt-solar-10.7b-sft-v5

Training Dataset

dpo+lora: 100k user preference set
We use A100 GPU 80GB * 8, when training.