README.md

metadata

license: apache-2.0
tags:
  - merge
  - mergekit
  - lazymergekit
  - samir-fama/SamirGPT-v1
  - abacusai/Slerp-CM-mist-dpo
  - EmbeddedLLM/Mistral-7B-Merge-14-v0.2

Daredevil-7B

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

• samir-fama/SamirGPT-v1
• abacusai/Slerp-CM-mist-dpo
• EmbeddedLLM/Mistral-7B-Merge-14-v0.2

🏆 Evaluation

Open LLM Leaderboard

TBD.

Nous

Model	AGIEval	GPT4All	TruthfulQA	Bigbench	Average
Daredevil-7B	44.85	76.07	64.89	47.07	58.22
OpenHermes-2.5-Mistral-7B	42.75	72.99	52.99	40.94	52.42
NeuralHermes-2.5-Mistral-7B	43.67	73.24	55.37	41.76	53.51
Marcoro14-7B-slerp	44.66	76.24	64.15	45.64	57.67
CatMarcoro14-7B-slerp	45.21	75.91	63.81	47.31	58.06
Nous-Hermes-2-SOLAR-10.7B	47.79	74.69	55.92	44.84	55.81

See the complete evaluation here.

🧩 Configuration

models:
  - model: mistralai/Mistral-7B-v0.1
    # No parameters necessary for base model
  - model: samir-fama/SamirGPT-v1
    parameters:
      density: 0.53
      weight: 0.4
  - model: abacusai/Slerp-CM-mist-dpo
    parameters:
      density: 0.53
      weight: 0.3
  - model: EmbeddedLLM/Mistral-7B-Merge-14-v0.2
    parameters:
      density: 0.53
      weight: 0.3
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "shadowml/Daredevil-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"])