CoolFace
Modelpublic

RichardErkhov/occultml_-_CatMarcoro14-7B-slerp-gguf

sourceHugging Faceupdated 2y agoView on Hugging Face
0likes307downloads
Model Card

Quantization made by Richard Erkhov.

Github

Discord

Request more models

CatMarcoro14-7B-slerp - GGUF

  • —Model creator: https://huggingface.co/occultml/
  • —Original model: https://huggingface.co/occultml/CatMarcoro14-7B-slerp/

Original model description: --- license: apache-2.0 tags:

  • —merge
  • —mergekit
  • —lazymergekit
  • —cookinai/CatMacaroni-Slerp
  • —EmbeddedLLM/Mistral-7B-Merge-14-v0.2 model-index:
  • —name: CatMarcoro14-7B-slerp results:
  • —task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2arc config: ARC-Challenge split: test args: numfew_shot: 25 metrics:
  • —type: accnorm value: 69.37 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllm_leaderboard?query=occultml/CatMarcoro14-7B-slerp name: Open LLM Leaderboard
  • —task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: numfewshot: 10 metrics:
  • —type: accnorm value: 86.92 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllm_leaderboard?query=occultml/CatMarcoro14-7B-slerp name: Open LLM Leaderboard
  • —task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: numfewshot: 5 metrics:
  • —type: acc value: 65.27 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=occultml/CatMarcoro14-7B-slerp name: Open LLM Leaderboard
  • —task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthfulqa config: multiplechoice split: validation args: numfewshot: 0 metrics:
  • —type: mc2 value: 63.24 source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=occultml/CatMarcoro14-7B-slerp name: Open LLM Leaderboard
  • —task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winograndexl split: validation args: numfew_shot: 5 metrics:
  • —type: acc value: 81.69 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=occultml/CatMarcoro14-7B-slerp name: Open LLM Leaderboard
  • —task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: numfewshot: 5 metrics:
  • —type: acc value: 73.01 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=occultml/CatMarcoro14-7B-slerp name: Open LLM Leaderboard ---

CatMarcoro14-7B-slerp

CatMarcoro14-7B-slerp is a merge of the following models using LazyMergekit:

🧩 Configuration

yaml
slices:
  - sources:
      - model: cookinai/CatMacaroni-Slerp
        layer_range: [0, 32]
      - model: EmbeddedLLM/Mistral-7B-Merge-14-v0.2
        layer_range: [0, 32]
merge_method: slerp
base_model: cookinai/CatMacaroni-Slerp
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

python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "occultml/CatMarcoro14-7B-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"])

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

MetricValue
Avg.73.25
AI2 Reasoning Challenge (25-Shot)69.37
HellaSwag (10-Shot)86.92
MMLU (5-Shot)65.27
TruthfulQA (0-shot)63.24
Winogrande (5-shot)81.69
GSM8k (5-shot)73.01