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RichardErkhov/Yhyu13_-_LMCocktail-10.7B-v1-gguf
Yhyu13_-_LMCocktail-10.7B-v1-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
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.gguf141 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
LMCocktail-10.7B-v1 - GGUF
| Name | Quant method | Size |
|---|---|---|
| LMCocktail-10.7B-v1.Q2_K.gguf | Q2_K | 3.73GB |
| LMCocktail-10.7B-v1.IQ3_XS.gguf | IQ3_XS | 4.14GB |
| LMCocktail-10.7B-v1.IQ3_S.gguf | IQ3_S | 4.37GB |
| LMCocktail-10.7B-v1.Q3_K_S.gguf | Q3_K_S | 4.34GB |
| LMCocktail-10.7B-v1.IQ3_M.gguf | IQ3_M | 4.51GB |
| LMCocktail-10.7B-v1.Q3_K.gguf | Q3_K | 4.84GB |
| LMCocktail-10.7B-v1.Q3_K_M.gguf | Q3_K_M | 4.84GB |
| LMCocktail-10.7B-v1.Q3_K_L.gguf | Q3_K_L | 5.26GB |
| LMCocktail-10.7B-v1.IQ4_XS.gguf | IQ4_XS | 5.43GB |
| LMCocktail-10.7B-v1.Q4_0.gguf | Q4_0 | 5.66GB |
| LMCocktail-10.7B-v1.IQ4_NL.gguf | IQ4_NL | 5.72GB |
| LMCocktail-10.7B-v1.Q4_K_S.gguf | Q4_K_S | 5.7GB |
| LMCocktail-10.7B-v1.Q4_K.gguf | Q4_K | 6.02GB |
| LMCocktail-10.7B-v1.Q4_K_M.gguf | Q4_K_M | 6.02GB |
| LMCocktail-10.7B-v1.Q4_1.gguf | Q4_1 | 6.27GB |
| LMCocktail-10.7B-v1.Q5_0.gguf | Q5_0 | 6.89GB |
| LMCocktail-10.7B-v1.Q5_K_S.gguf | Q5_K_S | 6.89GB |
| LMCocktail-10.7B-v1.Q5_K.gguf | Q5_K | 7.08GB |
| LMCocktail-10.7B-v1.Q5_K_M.gguf | Q5_K_M | 7.08GB |
| LMCocktail-10.7B-v1.Q5_1.gguf | Q5_1 | 7.51GB |
| LMCocktail-10.7B-v1.Q6_K.gguf | Q6_K | 8.2GB |
| LMCocktail-10.7B-v1.Q8_0.gguf | Q8_0 | 10.62GB |
This is a 50%-50% model of the SOLAR model and meow.
https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0
https://huggingface.co/rishiraj/meow
who rank #1 and #2 among models <13B in the https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard by 2023/12/20.
I am thrilled to announce that ChatGPT has ranked LMCocktail 10.7B as the second best model next to GPT4 on AlpcaEval in my local community run. You can also check the leaderboard at ./alpaca_eval/chatgpt_fn_--SOLAR-10-7B-LMCocktail/
win_rate standard_error n_total avg_length
gpt4 73.79 1.54 805 1365
SOLAR-10.7B-LMCocktail(new)73.45 1.56 804 1203
claude 70.37 1.60 805 1082
chatgpt 66.09 1.66 805 811
wizardlm-13b 65.16 1.67 805 985
vicuna-13b 64.10 1.69 805 1037
guanaco-65b 62.36 1.71 805 1249
oasst-rlhf-llama-33b 62.05 1.71 805 1079
alpaca-farm-ppo-human 60.25 1.72 805 803
falcon-40b-instruct 56.52 1.74 805 662
text_davinci_003 50.00 0.00 805 307
alpaca-7b 45.22 1.74 805 396
text_davinci_001 28.07 1.56 805 296
The LM-cocktail is novel technique for merging multiple models https://arxiv.org/abs/2311.13534
Code is backed up by this repo https://github.com/FlagOpen/FlagEmbedding.git
Merging scripts available under the ./scripts folder
The SOLAR model is the first model <30B that can answer this question from my test:
What will AI be like in the year 1010 A.D?
without hullicinating into 1010 A.D is a future time (like other llama2 models)
Models greater than that, like Yi-34B could answer this paradoxic question correctly as well, since it is huge enough.


