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DopeorNope_-_SOLARC-M-10.7B-gguf
RichardErkhov/DopeorNope_-_SOLARC-M-10.7B-gguf
DopeorNope_-_SOLARC-M-10.7B-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.
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Repo size
122 GB
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.gguf141 GB · 100%
At a glance
- Access
- Public
- Created
- Jul 23, 2024
- Updated
- Jul 23, 2024
- SHA
- fa3db218
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
SOLARC-M-10.7B - GGUF
- Model creator: https://huggingface.co/DopeorNope/
- Original model: https://huggingface.co/DopeorNope/SOLARC-M-10.7B/
| Name | Quant method | Size |
|---|---|---|
| SOLARC-M-10.7B.Q2_K.gguf | Q2_K | 3.73GB |
| SOLARC-M-10.7B.IQ3_XS.gguf | IQ3_XS | 4.14GB |
| SOLARC-M-10.7B.IQ3_S.gguf | IQ3_S | 4.37GB |
| SOLARC-M-10.7B.Q3_K_S.gguf | Q3_K_S | 4.34GB |
| SOLARC-M-10.7B.IQ3_M.gguf | IQ3_M | 4.51GB |
| SOLARC-M-10.7B.Q3_K.gguf | Q3_K | 4.84GB |
| SOLARC-M-10.7B.Q3_K_M.gguf | Q3_K_M | 4.84GB |
| SOLARC-M-10.7B.Q3_K_L.gguf | Q3_K_L | 5.26GB |
| SOLARC-M-10.7B.IQ4_XS.gguf | IQ4_XS | 5.43GB |
| SOLARC-M-10.7B.Q4_0.gguf | Q4_0 | 5.66GB |
| SOLARC-M-10.7B.IQ4_NL.gguf | IQ4_NL | 5.72GB |
| SOLARC-M-10.7B.Q4_K_S.gguf | Q4_K_S | 5.7GB |
| SOLARC-M-10.7B.Q4_K.gguf | Q4_K | 6.02GB |
| SOLARC-M-10.7B.Q4_K_M.gguf | Q4_K_M | 6.02GB |
| SOLARC-M-10.7B.Q4_1.gguf | Q4_1 | 6.27GB |
| SOLARC-M-10.7B.Q5_0.gguf | Q5_0 | 6.89GB |
| SOLARC-M-10.7B.Q5_K_S.gguf | Q5_K_S | 6.89GB |
| SOLARC-M-10.7B.Q5_K.gguf | Q5_K | 7.08GB |
| SOLARC-M-10.7B.Q5_K_M.gguf | Q5_K_M | 7.08GB |
| SOLARC-M-10.7B.Q5_1.gguf | Q5_1 | 7.51GB |
| SOLARC-M-10.7B.Q6_K.gguf | Q6_K | 8.2GB |
| SOLARC-M-10.7B.Q8_0.gguf | Q8_0 | 10.62GB |
Original model description:
language:
- ko library_name: transformers pipeline_tag: text-generation license: cc-by-nc-sa-4.0 tags:
- merge
The license is cc-by-nc-sa-4.0.
🐻❄️SOLARC-M-10.7B🐻❄️
Model Details
Model Developers Seungyoo Lee(DopeorNope)
I am in charge of Large Language Models (LLMs) at Markr AI team in South Korea.
Input Models input text only.
Output Models generate text only.
Model Architecture
SOLARC-M-10.7B is an auto-regressive language model based on the SOLAR architecture.
Base Model
kyujinpy/Sakura-SOLAR-Instruct
jeonsworld/CarbonVillain-en-10.7B-v1
Implemented Method
I have built a model using the merge method, utilizing each of these models as the base.
Implementation Code
Load model
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
repo = "DopeorNope/SOLARC-M-10.7B"
OpenOrca = AutoModelForCausalLM.from_pretrained(
repo,
return_dict=True,
torch_dtype=torch.float16,
device_map='auto'
)
OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
- Created
- Jul 23, 2024
- Updated
- Jul 23, 2024