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TW
J.O.S.I.E.3 Beta12 7B Slerp
J.O.S.I.E.3-Beta12-7B-slerp 是一個通過合併 Weyaxi/Einstein-v6-7B 和 argilla/CapybaraHermes-2.5-Mistral-7B 模型而成的7B參數大語言模型，支持多語言交互，採用ChatML提示格式。
下載量 17
發布時間 : 4/23/2024
模型概述
該模型是一個私人超級智能AI助手，專注於提供高質量的對話和問答服務，支持多種語言和複雜任務處理。
模型特點
多語言支持
支持包括中文在內的6種語言交互
合併模型優勢
結合Einstein-v6和CapybaraHermes兩個模型的優勢，通過slerp方法合併
ChatML格式
採用標準化的ChatML提示格式，便於集成到對話系統中
量化支持
提供GGUF量化版本，便於在不同硬件上部署
模型能力
多語言文本生成
智能對話
知識問答
任務完成
使用案例
個人助手
私人AI助手
作為個人日常助手，回答各種問題並提供建議
在HellaSwag測試集上達到83.98%的歸一化準確率
教育
學科知識問答
回答高中和大學水平的各學科問題
在高中地理測試中達到79.8%準確率
🚀 J.O.S.I.E.3-Beta12-7B-slerp
J.O.S.I.E.3-Beta12-7B-slerp 是一個融合模型，它使用 LazyMergekit 對以下模型進行了融合：
該模型在自定義的 J.O.S.I.E.v3.11 數據集上進行了進一步微調，採用 ChatML 提示格式。
<|im_start|>system
You are JOSIE, my private and superinteligent AI Assistant.<|im_end|>
<|im_start|>user
{{ .Prompt }}<|im_end|>
<|im_start|>assistant
{{ .Response }}<|im_end|>
🚀 快速開始
在 ollama 中運行
ollama run goekdenizguelmez/j.o.s.i.e.v3-beta12.1
目前僅支持 q4-k-m 量化版本！
✨ 主要特性
- 融合了多個優秀模型的能力。
- 在自定義數據集上進行微調，以適應特定的任務和場景。
- 支持多種語言，包括英語、德語、西班牙語、法語、日語和中文。
📦 安裝指南
安裝依賴
!pip install -qU transformers accelerate
💻 使用示例
基礎用法
from transformers import AutoTokenizer
import transformers
import torch
model = "Isaak-Carter/J.O.S.I.E.3-Beta12-7B-slerp"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
📚 詳細文檔
🧩 配置信息
slices:
- sources:
- model: Weyaxi/Einstein-v6-7B
layer_range: [0, 32]
- model: argilla/CapybaraHermes-2.5-Mistral-7B
layer_range: [0, 32]
merge_method: slerp
base_model: argilla/CapybaraHermes-2.5-Mistral-7B
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
評估結果
{
"all": {
"acc": 0.635008846776534,
"acc_stderr": 0.03244450973873997,
"acc_norm": 0.6365238167399629,
"acc_norm_stderr": 0.033101612504829854,
"mc1": 0.397796817625459,
"mc1_stderr": 0.017133934248559635,
"mc2": 0.5816259277988214,
"mc2_stderr": 0.01521267822060948
},
"harness|arc:challenge|25": {
"acc": 0.6220136518771331,
"acc_stderr": 0.0141696645203031,
"acc_norm": 0.6459044368600683,
"acc_norm_stderr": 0.013975454122756557
},
"harness|hellaswag|10": {
"acc": 0.6512646883091018,
"acc_stderr": 0.004755960559929163,
"acc_norm": 0.8397729535949015,
"acc_norm_stderr": 0.003660668242740655
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.4,
"acc_stderr": 0.04923659639173309,
"acc_norm": 0.4,
"acc_norm_stderr": 0.04923659639173309
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.5703703703703704,
"acc_stderr": 0.042763494943765995,
"acc_norm": 0.5703703703703704,
"acc_norm_stderr": 0.042763494943765995
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.6842105263157895,
"acc_stderr": 0.0378272898086547,
"acc_norm": 0.6842105263157895,
"acc_norm_stderr": 0.0378272898086547
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.58,
"acc_stderr": 0.049604496374885836,
"acc_norm": 0.58,
"acc_norm_stderr": 0.049604496374885836
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.6792452830188679,
"acc_stderr": 0.028727502957880267,
"acc_norm": 0.6792452830188679,
"acc_norm_stderr": 0.028727502957880267
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.7361111111111112,
"acc_stderr": 0.03685651095897532,
"acc_norm": 0.7361111111111112,
"acc_norm_stderr": 0.03685651095897532
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.54,
"acc_stderr": 0.05009082659620332,
"acc_norm": 0.54,
"acc_norm_stderr": 0.05009082659620332
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.51,
"acc_stderr": 0.05024183937956912,
"acc_norm": 0.51,
"acc_norm_stderr": 0.05024183937956912
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.29,
"acc_stderr": 0.04560480215720684,
"acc_norm": 0.29,
"acc_norm_stderr": 0.04560480215720684
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.6416184971098265,
"acc_stderr": 0.036563436533531585,
"acc_norm": 0.6416184971098265,
"acc_norm_stderr": 0.036563436533531585
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.3235294117647059,
"acc_stderr": 0.04655010411319619,
"acc_norm": 0.3235294117647059,
"acc_norm_stderr": 0.04655010411319619
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.76,
"acc_stderr": 0.04292346959909283,
"acc_norm": 0.76,
"acc_norm_stderr": 0.04292346959909283
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.5829787234042553,
"acc_stderr": 0.03223276266711712,
"acc_norm": 0.5829787234042553,
"acc_norm_stderr": 0.03223276266711712
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.4649122807017544,
"acc_stderr": 0.046920083813689104,
"acc_norm": 0.4649122807017544,
"acc_norm_stderr": 0.046920083813689104
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.5517241379310345,
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"acc_norm": 0.5517241379310345,
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},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.42063492063492064,
"acc_stderr": 0.025424835086924006,
"acc_norm": 0.42063492063492064,
"acc_norm_stderr": 0.025424835086924006
},
"harness|hendrycksTest-formal_logic|5": {
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"harness|hendrycksTest-global_facts|5": {
"acc": 0.44,
"acc_stderr": 0.04988876515698589,
"acc_norm": 0.44,
"acc_norm_stderr": 0.04988876515698589
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.7548387096774194,
"acc_stderr": 0.024472243840895525,
"acc_norm": 0.7548387096774194,
"acc_norm_stderr": 0.024472243840895525
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.5024630541871922,
"acc_stderr": 0.035179450386910616,
"acc_norm": 0.5024630541871922,
"acc_norm_stderr": 0.035179450386910616
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.66,
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"acc_norm": 0.66,
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},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.7818181818181819,
"acc_stderr": 0.03225078108306289,
"acc_norm": 0.7818181818181819,
"acc_norm_stderr": 0.03225078108306289
},
"harness|hendrycksTest-high_school_geography|5": {
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"acc_norm": 0.797979797979798,
"acc_norm_stderr": 0.02860620428922988
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.8756476683937824,
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"acc_norm": 0.8756476683937824,
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},
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"acc_norm": 0.658974358974359,
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},
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"acc_stderr": 0.02857834836547308,
"acc_norm": 0.32592592592592595,
"acc_norm_stderr": 0.02857834836547308
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.6638655462184874,
"acc_stderr": 0.030684737115135363,
"acc_norm": 0.6638655462184874,
"acc_norm_stderr": 0.030684737115135363
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.304635761589404,
"acc_stderr": 0.03757949922943344,
"acc_norm": 0.304635761589404,
"acc_norm_stderr": 0.03757949922943344
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.8238532110091743,
"acc_stderr": 0.016332882393431353,
"acc_norm": 0.8238532110091743,
"acc_norm_stderr": 0.016332882393431353
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.5092592592592593,
"acc_stderr": 0.03409386946992699,
"acc_norm": 0.5092592592592593,
"acc_norm_stderr": 0.03409386946992699
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.7990196078431373,
"acc_stderr": 0.02812597226565437,
"acc_norm": 0.7990196078431373,
"acc_norm_stderr": 0.02812597226565437
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.759493670886076,
"acc_stderr": 0.027820781981149685,
"acc_norm": 0.759493670886076,
"acc_norm_stderr": 0.027820781981149685
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.6681614349775785,
"acc_stderr": 0.03160295143776679,
"acc_norm": 0.6681614349775785,
"acc_norm_stderr": 0.03160295143776679
},
"harness|hendrycksTest-human_sexuality|5": {
"acc": 0.7404580152671756,
"acc_stderr": 0.03844876139785271,
"acc_norm": 0.7404580152671756,
"acc_norm_stderr": 0.03844876139785271
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.8016528925619835,
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"acc_norm": 0.8016528925619835,
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"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.7777777777777778,
"acc_stderr": 0.040191074725573483,
"acc_norm": 0.7777777777777778,
"acc_norm_stderr": 0.040191074725573483
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"harness|hendrycksTest-logical_fallacies|5": {
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"acc_norm": 0.754601226993865,
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"harness|hendrycksTest-management|5": {
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"acc_norm": 0.7766990291262136,
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"harness|hendrycksTest-marketing|5": {
"acc": 0.8632478632478633,
"acc_stderr": 0.022509033937077802,
"acc_norm": 0.8632478632478633,
"acc_norm_stderr": 0.022509033937077802
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"harness|hendrycksTest-medical_genetics|5": {
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"harness|hendrycksTest-moral_disputes|5": {
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"acc_norm": 0.7254335260115607,
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"acc_norm": 0.27039106145251396,
"acc_norm_stderr": 0.014854993938010071
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"harness|hendrycksTest-nutrition|5": {
"acc": 0.7516339869281046,
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"acc_norm": 0.7516339869281046,
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"harness|hendrycksTest-philosophy|5": {
"acc": 0.7331189710610932,
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"acc_norm": 0.7331189710610932,
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"harness|hendrycksTest-prehistory|5": {
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"harness|hendrycksTest-professional_accounting|5": {
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"acc_norm": 0.46099290780141844,
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"harness|hendrycksTest-professional_law|5": {
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"harness|hendrycksTest-public_relations|5": {
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"harness|hendrycksTest-security_studies|5": {
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"acc_stderr": 0.029822533793982062,
"acc_norm": 0.6816326530612244,
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"harness|hendrycksTest-sociology|5": {
"acc": 0.8507462686567164,
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"acc_norm": 0.8507462686567164,
"acc_norm_stderr": 0.025196929874827072
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"harness|hendrycksTest-us_foreign_policy|5": {
"acc": 0.85,
"acc_stderr": 0.035887028128263734,
"acc_norm": 0.85,
"acc_norm_stderr": 0.035887028128263734
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"harness|hendrycksTest-virology|5": {
"acc": 0.5180722891566265,
"acc_stderr": 0.03889951252827216,
"acc_norm": 0.5180722891566265,
"acc_norm_stderr": 0.03889951252827216
},
"harness|hendrycksTest-world_religions|5": {
"acc": 0.8362573099415205,
"acc_stderr": 0.028380919596145866,
"acc_norm": 0.8362573099415205,
"acc_norm_stderr": 0.028380919596145866
},
"harness|truthfulqa:mc|0": {
"mc1": 0.397796817625459,
"mc1_stderr": 0.017133934248559635,
"mc2": 0.5816259277988214,
"mc2_stderr": 0.01521267822060948
},
"harness|winogrande|5": {
"acc": 0.7963693764798737,
"acc_stderr": 0.011317798781626913
},
"harness|gsm8k|5": {
"acc": 0.5966641394996209,
"acc_stderr": 0.013512654781814702
}
}
📄 許可證
本項目採用 Apache-2.0 許可證。
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