RichardErkhov/mayacinka_-_yam-sam-7B-gguf

Quantization made by Richard Erkhov.

Github

Discord

Request more models

yam-sam-7B - GGUF

• —Model creator: https://huggingface.co/mayacinka/
• —Original model: https://huggingface.co/mayacinka/yam-sam-7B/

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

• —merge
• —mergekit
• —lazymergekit
• —cognitivecomputations/samantha-mistral-7b
• —CorticalStack/shadow-clown-7B-dare
• —yam-peleg/Experiment26-7B base_model:
• —cognitivecomputations/samantha-mistral-7b
• —CorticalStack/shadow-clown-7B-dare
• —yam-peleg/Experiment26-7B model-index:
• —name: yam-sam-7B 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: 70.9 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllm_leaderboard?query=mayacinka/yam-sam-7B 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: 87.92 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllm_leaderboard?query=mayacinka/yam-sam-7B 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: 65.39 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=mayacinka/yam-sam-7B 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: 71.3 source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=mayacinka/yam-sam-7B 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: 83.03 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=mayacinka/yam-sam-7B 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: 68.92 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=mayacinka/yam-sam-7B name: Open LLM Leaderboard ---

yam-sam-7B

yam-sam-7B is a merge of the following models using LazyMergekit:

• —cognitivecomputations/samantha-mistral-7b
• —CorticalStack/shadow-clown-7B-dare
• —yam-peleg/Experiment26-7B

🧩 Configuration

models:
  - model: yam-peleg/Experiment27-7B
    # No parameters necessary for base model
  - model: cognitivecomputations/samantha-mistral-7b
    parameters:
      weight: 0.3
      density: 0.8
  - model: CorticalStack/shadow-clown-7B-dare
    parameters:
      weight: 0.1
      density: 0.8
  - model: yam-peleg/Experiment26-7B
    parameters:
      weight: 0.6
      density: 0.8
merge_method: dare_ties
base_model: yam-peleg/Experiment27-7B
parameters:
  int8_mask: true
dtype: bfloat16
random_seed: 0

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "mayacinka/yam-sam-7B"
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