Hugging Face's logo

Goekdeniz-Guelmez
/
J.O.S.I.E.3-Beta3-slerp

Text Generation
Transformers
Safetensors
mistral
Merge
mergekit
lazymergekit
Locutusque/Hercules-3.1-Mistral-7B
cognitivecomputations/dolphin-2.8-experiment26-7b
text-generation-inference
Inference Endpoints
Model card Files Community
Edit model card

JOSIE_Beta-3-7B-slerp

JOSIE_Beta-3-7B-slerp is a merge of the following models using LazyMergekit:

IMPORTANT!!!

upon sseing the eval bechmarks on the LLM Leaderboard, this is the best performing model, but it's not uncensored, and it's answers are not really good when chatting with it. I will further train it one datasets like dolphin and other.

{
    "all": {
        "acc": 0.6432209013684985,
        "acc_stderr": 0.03221665824377992,
        "acc_norm": 0.6450099678239628,
        "acc_norm_stderr": 0.032867717920871294,
        "mc1": 0.3353733170134639,
        "mc1_stderr": 0.01652753403966899,
        "mc2": 0.48804542326643174,
        "mc2_stderr": 0.015087630632446147
    },
    "harness|arc:challenge|25": {
        "acc": 0.6083617747440273,
        "acc_stderr": 0.014264122124938217,
        "acc_norm": 0.6339590443686007,
        "acc_norm_stderr": 0.014077223108470139
    },
    "harness|hellaswag|10": {
        "acc": 0.6618203545110536,
        "acc_stderr": 0.0047212316370927225,
        "acc_norm": 0.8456482772356104,
        "acc_norm_stderr": 0.0036054721167622867
    },
    "harness|hendrycksTest-abstract_algebra|5": {
        "acc": 0.3,
        "acc_stderr": 0.046056618647183814,
        "acc_norm": 0.3,
        "acc_norm_stderr": 0.046056618647183814
    },
    "harness|hendrycksTest-anatomy|5": {
        "acc": 0.6074074074074074,
        "acc_stderr": 0.04218506215368879,
        "acc_norm": 0.6074074074074074,
        "acc_norm_stderr": 0.04218506215368879
    },
    "harness|hendrycksTest-astronomy|5": {
        "acc": 0.6710526315789473,
        "acc_stderr": 0.03823428969926605,
        "acc_norm": 0.6710526315789473,
        "acc_norm_stderr": 0.03823428969926605
    },
    "harness|hendrycksTest-business_ethics|5": {
        "acc": 0.61,
        "acc_stderr": 0.04902071300001975,
        "acc_norm": 0.61,
        "acc_norm_stderr": 0.04902071300001975
    },
    "harness|hendrycksTest-clinical_knowledge|5": {
        "acc": 0.7018867924528301,
        "acc_stderr": 0.02815283794249387,
        "acc_norm": 0.7018867924528301,
        "acc_norm_stderr": 0.02815283794249387
    },
    "harness|hendrycksTest-college_biology|5": {
        "acc": 0.7638888888888888,
        "acc_stderr": 0.03551446610810826,
        "acc_norm": 0.7638888888888888,
        "acc_norm_stderr": 0.03551446610810826
    },
    "harness|hendrycksTest-college_chemistry|5": {
        "acc": 0.44,
        "acc_stderr": 0.04988876515698589,
        "acc_norm": 0.44,
        "acc_norm_stderr": 0.04988876515698589
    },
    "harness|hendrycksTest-college_computer_science|5": {
        "acc": 0.52,
        "acc_stderr": 0.050211673156867795,
        "acc_norm": 0.52,
        "acc_norm_stderr": 0.050211673156867795
    },
    "harness|hendrycksTest-college_mathematics|5": {
        "acc": 0.37,
        "acc_stderr": 0.04852365870939099,
        "acc_norm": 0.37,
        "acc_norm_stderr": 0.04852365870939099
    },
    "harness|hendrycksTest-college_medicine|5": {
        "acc": 0.6473988439306358,
        "acc_stderr": 0.03643037168958548,
        "acc_norm": 0.6473988439306358,
        "acc_norm_stderr": 0.03643037168958548
    },
    "harness|hendrycksTest-college_physics|5": {
        "acc": 0.38235294117647056,
        "acc_stderr": 0.04835503696107223,
        "acc_norm": 0.38235294117647056,
        "acc_norm_stderr": 0.04835503696107223
    },
    "harness|hendrycksTest-computer_security|5": {
        "acc": 0.75,
        "acc_stderr": 0.04351941398892446,
        "acc_norm": 0.75,
        "acc_norm_stderr": 0.04351941398892446
    },
    "harness|hendrycksTest-conceptual_physics|5": {
        "acc": 0.574468085106383,
        "acc_stderr": 0.03232146916224468,
        "acc_norm": 0.574468085106383,
        "acc_norm_stderr": 0.03232146916224468
    },
    "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": 0.5310344827586206,
        "acc_stderr": 0.04158632762097828,
        "acc_norm": 0.5310344827586206,
        "acc_norm_stderr": 0.04158632762097828
    },
    "harness|hendrycksTest-elementary_mathematics|5": {
        "acc": 0.41534391534391535,
        "acc_stderr": 0.025379524910778405,
        "acc_norm": 0.41534391534391535,
        "acc_norm_stderr": 0.025379524910778405
    },
    "harness|hendrycksTest-formal_logic|5": {
        "acc": 0.46825396825396826,
        "acc_stderr": 0.04463112720677171,
        "acc_norm": 0.46825396825396826,
        "acc_norm_stderr": 0.04463112720677171
    },
    "harness|hendrycksTest-global_facts|5": {
        "acc": 0.35,
        "acc_stderr": 0.0479372485441102,
        "acc_norm": 0.35,
        "acc_norm_stderr": 0.0479372485441102
    },
    "harness|hendrycksTest-high_school_biology|5": {
        "acc": 0.7709677419354839,
        "acc_stderr": 0.023904914311782648,
        "acc_norm": 0.7709677419354839,
        "acc_norm_stderr": 0.023904914311782648
    },
    "harness|hendrycksTest-high_school_chemistry|5": {
        "acc": 0.5073891625615764,
        "acc_stderr": 0.035176035403610105,
        "acc_norm": 0.5073891625615764,
        "acc_norm_stderr": 0.035176035403610105
    },
    "harness|hendrycksTest-high_school_computer_science|5": {
        "acc": 0.69,
        "acc_stderr": 0.04648231987117316,
        "acc_norm": 0.69,
        "acc_norm_stderr": 0.04648231987117316
    },
    "harness|hendrycksTest-high_school_european_history|5": {
        "acc": 0.7757575757575758,
        "acc_stderr": 0.032568666616811015,
        "acc_norm": 0.7757575757575758,
        "acc_norm_stderr": 0.032568666616811015
    },
    "harness|hendrycksTest-high_school_geography|5": {
        "acc": 0.797979797979798,
        "acc_stderr": 0.028606204289229872,
        "acc_norm": 0.797979797979798,
        "acc_norm_stderr": 0.028606204289229872
    },
    "harness|hendrycksTest-high_school_government_and_politics|5": {
        "acc": 0.8963730569948186,
        "acc_stderr": 0.02199531196364424,
        "acc_norm": 0.8963730569948186,
        "acc_norm_stderr": 0.02199531196364424
    },
    "harness|hendrycksTest-high_school_macroeconomics|5": {
        "acc": 0.6641025641025641,
        "acc_stderr": 0.023946724741563973,
        "acc_norm": 0.6641025641025641,
        "acc_norm_stderr": 0.023946724741563973
    },
    "harness|hendrycksTest-high_school_mathematics|5": {
        "acc": 0.3888888888888889,
        "acc_stderr": 0.029723278961476664,
        "acc_norm": 0.3888888888888889,
        "acc_norm_stderr": 0.029723278961476664
    },
    "harness|hendrycksTest-high_school_microeconomics|5": {
        "acc": 0.680672268907563,
        "acc_stderr": 0.030283995525884396,
        "acc_norm": 0.680672268907563,
        "acc_norm_stderr": 0.030283995525884396
    },
    "harness|hendrycksTest-high_school_physics|5": {
        "acc": 0.3443708609271523,
        "acc_stderr": 0.038796870240733264,
        "acc_norm": 0.3443708609271523,
        "acc_norm_stderr": 0.038796870240733264
    },
    "harness|hendrycksTest-high_school_psychology|5": {
        "acc": 0.8422018348623853,
        "acc_stderr": 0.01563002297009245,
        "acc_norm": 0.8422018348623853,
        "acc_norm_stderr": 0.01563002297009245
    },
    "harness|hendrycksTest-high_school_statistics|5": {
        "acc": 0.5,
        "acc_stderr": 0.034099716973523674,
        "acc_norm": 0.5,
        "acc_norm_stderr": 0.034099716973523674
    },
    "harness|hendrycksTest-high_school_us_history|5": {
        "acc": 0.7990196078431373,
        "acc_stderr": 0.028125972265654366,
        "acc_norm": 0.7990196078431373,
        "acc_norm_stderr": 0.028125972265654366
    },
    "harness|hendrycksTest-high_school_world_history|5": {
        "acc": 0.7890295358649789,
        "acc_stderr": 0.02655837250266192,
        "acc_norm": 0.7890295358649789,
        "acc_norm_stderr": 0.02655837250266192
    },
    "harness|hendrycksTest-human_aging|5": {
        "acc": 0.695067264573991,
        "acc_stderr": 0.030898610882477515,
        "acc_norm": 0.695067264573991,
        "acc_norm_stderr": 0.030898610882477515
    },
    "harness|hendrycksTest-human_sexuality|5": {
        "acc": 0.7862595419847328,
        "acc_stderr": 0.0359546161177469,
        "acc_norm": 0.7862595419847328,
        "acc_norm_stderr": 0.0359546161177469
    },
    "harness|hendrycksTest-international_law|5": {
        "acc": 0.8016528925619835,
        "acc_stderr": 0.036401182719909476,
        "acc_norm": 0.8016528925619835,
        "acc_norm_stderr": 0.036401182719909476
    },
    "harness|hendrycksTest-jurisprudence|5": {
        "acc": 0.7870370370370371,
        "acc_stderr": 0.0395783547198098,
        "acc_norm": 0.7870370370370371,
        "acc_norm_stderr": 0.0395783547198098
    },
    "harness|hendrycksTest-logical_fallacies|5": {
        "acc": 0.754601226993865,
        "acc_stderr": 0.03380939813943354,
        "acc_norm": 0.754601226993865,
        "acc_norm_stderr": 0.03380939813943354
    },
    "harness|hendrycksTest-machine_learning|5": {
        "acc": 0.5535714285714286,
        "acc_stderr": 0.04718471485219587,
        "acc_norm": 0.5535714285714286,
        "acc_norm_stderr": 0.04718471485219587
    },
    "harness|hendrycksTest-management|5": {
        "acc": 0.7766990291262136,
        "acc_stderr": 0.04123553189891431,
        "acc_norm": 0.7766990291262136,
        "acc_norm_stderr": 0.04123553189891431
    },
    "harness|hendrycksTest-marketing|5": {
        "acc": 0.8760683760683761,
        "acc_stderr": 0.021586494001281376,
        "acc_norm": 0.8760683760683761,
        "acc_norm_stderr": 0.021586494001281376
    },
    "harness|hendrycksTest-medical_genetics|5": {
        "acc": 0.74,
        "acc_stderr": 0.04408440022768079,
        "acc_norm": 0.74,
        "acc_norm_stderr": 0.04408440022768079
    },
    "harness|hendrycksTest-miscellaneous|5": {
        "acc": 0.8186462324393359,
        "acc_stderr": 0.01377869377846408,
        "acc_norm": 0.8186462324393359,
        "acc_norm_stderr": 0.01377869377846408
    },
    "harness|hendrycksTest-moral_disputes|5": {
        "acc": 0.7225433526011561,
        "acc_stderr": 0.024105712607754307,
        "acc_norm": 0.7225433526011561,
        "acc_norm_stderr": 0.024105712607754307
    },
    "harness|hendrycksTest-moral_scenarios|5": {
        "acc": 0.288268156424581,
        "acc_stderr": 0.015149132860209432,
        "acc_norm": 0.288268156424581,
        "acc_norm_stderr": 0.015149132860209432
    },
    "harness|hendrycksTest-nutrition|5": {
        "acc": 0.7189542483660131,
        "acc_stderr": 0.025738854797818733,
        "acc_norm": 0.7189542483660131,
        "acc_norm_stderr": 0.025738854797818733
    },
    "harness|hendrycksTest-philosophy|5": {
        "acc": 0.7170418006430869,
        "acc_stderr": 0.025583062489984813,
        "acc_norm": 0.7170418006430869,
        "acc_norm_stderr": 0.025583062489984813
    },
    "harness|hendrycksTest-prehistory|5": {
        "acc": 0.7407407407407407,
        "acc_stderr": 0.024383665531035457,
        "acc_norm": 0.7407407407407407,
        "acc_norm_stderr": 0.024383665531035457
    },
    "harness|hendrycksTest-professional_accounting|5": {
        "acc": 0.5035460992907801,
        "acc_stderr": 0.02982674915328092,
        "acc_norm": 0.5035460992907801,
        "acc_norm_stderr": 0.02982674915328092
    },
    "harness|hendrycksTest-professional_law|5": {
        "acc": 0.4680573663624511,
        "acc_stderr": 0.012744149704869647,
        "acc_norm": 0.4680573663624511,
        "acc_norm_stderr": 0.012744149704869647
    },
    "harness|hendrycksTest-professional_medicine|5": {
        "acc": 0.6838235294117647,
        "acc_stderr": 0.028245687391462927,
        "acc_norm": 0.6838235294117647,
        "acc_norm_stderr": 0.028245687391462927
    },
    "harness|hendrycksTest-professional_psychology|5": {
        "acc": 0.6633986928104575,
        "acc_stderr": 0.019117213911495158,
        "acc_norm": 0.6633986928104575,
        "acc_norm_stderr": 0.019117213911495158
    },
    "harness|hendrycksTest-public_relations|5": {
        "acc": 0.6636363636363637,
        "acc_stderr": 0.04525393596302506,
        "acc_norm": 0.6636363636363637,
        "acc_norm_stderr": 0.04525393596302506
    },
    "harness|hendrycksTest-security_studies|5": {
        "acc": 0.7428571428571429,
        "acc_stderr": 0.027979823538744546,
        "acc_norm": 0.7428571428571429,
        "acc_norm_stderr": 0.027979823538744546
    },
    "harness|hendrycksTest-sociology|5": {
        "acc": 0.845771144278607,
        "acc_stderr": 0.025538433368578337,
        "acc_norm": 0.845771144278607,
        "acc_norm_stderr": 0.025538433368578337
    },
    "harness|hendrycksTest-us_foreign_policy|5": {
        "acc": 0.87,
        "acc_stderr": 0.033799766898963086,
        "acc_norm": 0.87,
        "acc_norm_stderr": 0.033799766898963086
    },
    "harness|hendrycksTest-virology|5": {
        "acc": 0.5301204819277109,
        "acc_stderr": 0.03885425420866767,
        "acc_norm": 0.5301204819277109,
        "acc_norm_stderr": 0.03885425420866767
    },
    "harness|hendrycksTest-world_religions|5": {
        "acc": 0.8128654970760234,
        "acc_stderr": 0.02991312723236804,
        "acc_norm": 0.8128654970760234,
        "acc_norm_stderr": 0.02991312723236804
    },
    "harness|truthfulqa:mc|0": {
        "mc1": 0.3353733170134639,
        "mc1_stderr": 0.01652753403966899,
        "mc2": 0.48804542326643174,
        "mc2_stderr": 0.015087630632446147
    },
    "harness|winogrande|5": {
        "acc": 0.8042620363062352,
        "acc_stderr": 0.011151145042218319
    },
    "harness|gsm8k|5": {
        "acc": 0.5860500379075056,
        "acc_stderr": 0.013566991960151778
    }
}

🧩 Configuration 

slices:
  - sources:
      - model: Locutusque/Hercules-3.1-Mistral-7B
        layer_range: [0, 32]
      - model: cognitivecomputations/dolphin-2.8-experiment26-7b
        layer_range: [0, 32]
merge_method: slerp
base_model: Locutusque/Hercules-3.1-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

💻 Usage 

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Isaak-Carter/JOSIE_Beta-3-7B-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"])
Downloads last month
33
Safetensors
Model size
7.24B params
Tensor type
BF16
·
Inference Examples
Text Generation
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for Goekdeniz-Guelmez/J.O.S.I.E.3-Beta3-slerp

Locutusque/Hercules-3.1-Mistral-7B
cognitivecomputations/dolphin-2.8-experiment26-7b
Merge model
this model
Merges
1 model