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RichardErkhov/beomi_-_Solar-Ko-Recovery-11B-gguf
beomi_-_Solar-Ko-Recovery-11B-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.
Downloads · 30 days
332
17% of all-time downloads
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.gguf145 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
Solar-Ko-Recovery-11B - GGUF
| Name | Quant method | Size |
|---|---|---|
| Solar-Ko-Recovery-11B.Q2_K.gguf | Q2_K | 3.87GB |
| Solar-Ko-Recovery-11B.IQ3_XS.gguf | IQ3_XS | 4.29GB |
| Solar-Ko-Recovery-11B.IQ3_S.gguf | IQ3_S | 4.52GB |
| Solar-Ko-Recovery-11B.Q3_K_S.gguf | Q3_K_S | 4.5GB |
| Solar-Ko-Recovery-11B.IQ3_M.gguf | IQ3_M | 4.67GB |
| Solar-Ko-Recovery-11B.Q3_K.gguf | Q3_K | 4.99GB |
| Solar-Ko-Recovery-11B.Q3_K_M.gguf | Q3_K_M | 4.99GB |
| Solar-Ko-Recovery-11B.Q3_K_L.gguf | Q3_K_L | 5.42GB |
| Solar-Ko-Recovery-11B.IQ4_XS.gguf | IQ4_XS | 5.59GB |
| Solar-Ko-Recovery-11B.Q4_0.gguf | Q4_0 | 5.82GB |
| Solar-Ko-Recovery-11B.IQ4_NL.gguf | IQ4_NL | 5.89GB |
| Solar-Ko-Recovery-11B.Q4_K_S.gguf | Q4_K_S | 5.87GB |
| Solar-Ko-Recovery-11B.Q4_K.gguf | Q4_K | 6.19GB |
| Solar-Ko-Recovery-11B.Q4_K_M.gguf | Q4_K_M | 6.19GB |
| Solar-Ko-Recovery-11B.Q4_1.gguf | Q4_1 | 6.45GB |
| Solar-Ko-Recovery-11B.Q5_0.gguf | Q5_0 | 7.07GB |
| Solar-Ko-Recovery-11B.Q5_K_S.gguf | Q5_K_S | 7.07GB |
| Solar-Ko-Recovery-11B.Q5_K.gguf | Q5_K | 7.26GB |
| Solar-Ko-Recovery-11B.Q5_K_M.gguf | Q5_K_M | 7.26GB |
| Solar-Ko-Recovery-11B.Q5_1.gguf | Q5_1 | 7.7GB |
| Solar-Ko-Recovery-11B.Q6_K.gguf | Q6_K | 8.4GB |
| Solar-Ko-Recovery-11B.Q8_0.gguf | Q8_0 | 10.88GB |
language:
Update Log
Solar-Ko-Recovery-11B aimed to recover Solar's capability on Korean with re-arrange of Embeddings and LM head, featuring an expanded vocabulary and the inclusion of a Korean+English corpus for enhanced representation.
Model Developers: Junbum Lee (Beomi)
Variations: Solar-Ko-Recovery is available with one parameter sizes — 11B(10.99B🤣).
Input: The model accepts only text input.
Output: The model produces text output exclusively.
Model Architecture:
Solar-Ko-Recovery is an auto-regressive language model that leverages an optimized transformer architecture derived from Llama-2.
| Training Data | Parameters | Content Length | GQA | Tokens | Learning Rate | |
|---|---|---|---|---|---|---|
| Solar-Ko-Recovery | A curated mix of Korean+English Corpora | 10.8B | 4k | O | >30B* | 5e<sup>-5</sup> |
NOTE: Only Embedding layer and LM Head layer are trained.
Vocab Expansion
Vocab expansion is conducted on edited upstage/solar-1-mini-tokenizer, which is superset of Solar tokenizer.
| Model Name | Vocabulary Size | Description |
|---|---|---|
| Original Solar | 32000 | Sentencepiece BPE |
| solar-1-mini-tokenizer | 64000 | Sentencepiece BPE. Added Ko/JP vocabs |
Tokenizing "안녕하세요, 오늘은 날씨가 좋네요."
| Model | Tokens |
|---|---|
| SOLAR-10.7B | ['▁', '안', '<0xEB>', '<0x85>', '<0x95>', '하', '세', '요', ',', '▁', '오', '<0xEB>', '<0x8A>', '<0x98>', '은', '▁', '날', '<0xEC>', '<0x94>', '<0xA8>', '가', '▁', '좋', '네', '요', '.'] |
| Solar-Ko-Recovery | ['▁안녕하세요', ',', '▁오늘은', '▁날씨가', '▁좋', '네요', '.'] |
Tokenizing "Meet 10.7B Solar: Elevating Performance with Upstage Depth UP Scaling!"
| Model | Tokens |
|---|---|
| SOLAR-10.7B | ['▁Meet', '▁', '1', '0', '.', '7', 'B', '▁Solar', ':', '▁E', 'lev', 'ating', '▁Performance', '▁with', '▁Up', 'stage', '▁Dep', 'th', '▁UP', '▁Scal', 'ing', '!'] |
| Solar-Ko-Recovery | ['▁Meet', '▁', '1', '0', '.', '7', 'B', '▁Solar', ':', '▁E', 'lev', 'ating', '▁Performance', '▁with', '▁Up', 'stage', '▁Dep', 'th', '▁UP', '▁Scal', 'ing', '!'] |
Apache 2.0
TBD
TBD