README.md

metadata

license: cc-by-nc-4.0
tags:
  - merge
  - mergekit
  - lazymergekit
  - fblgit/UNA-TheBeagle-7b-v1
  - argilla/distilabeled-Marcoro14-7B-slerp
base_model:
  - fblgit/UNA-TheBeagle-7b-v1
  - argilla/distilabeled-Marcoro14-7B-slerp
model-index:
  - name: Beagle14-7B
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: AI2 Reasoning Challenge (25-Shot)
          type: ai2_arc
          config: ARC-Challenge
          split: test
          args:
            num_few_shot: 25
        metrics:
          - type: acc_norm
            value: 72.95
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Beagle14-7B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: HellaSwag (10-Shot)
          type: hellaswag
          split: validation
          args:
            num_few_shot: 10
        metrics:
          - type: acc_norm
            value: 87.95
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Beagle14-7B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU (5-Shot)
          type: cais/mmlu
          config: all
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 64.7
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Beagle14-7B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: TruthfulQA (0-shot)
          type: truthful_qa
          config: multiple_choice
          split: validation
          args:
            num_few_shot: 0
        metrics:
          - type: mc2
            value: 68.88
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Beagle14-7B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: Winogrande (5-shot)
          type: winogrande
          config: winogrande_xl
          split: validation
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 82.64
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Beagle14-7B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GSM8k (5-shot)
          type: gsm8k
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 71.42
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Beagle14-7B
          name: Open LLM Leaderboard

Beagle14-7B

Update 01/16/24: Check the DPO fine-tuned version of this model, NeuralBeagle14-7B (probably the best 7B model you can find)! 🎉

Beagle14-7B is a merge of the following models using LazyMergekit:

• fblgit/UNA-TheBeagle-7b-v1
• argilla/distilabeled-Marcoro14-7B-slerp

🏆 Evaluation

The evaluation was performed using LLM AutoEval on Nous suite.

Model	AGIEval	GPT4All	TruthfulQA	Bigbench	Average
Beagle14-7B	44.38	76.53	69.44	47.25	59.4
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
Nous-Hermes-2-SOLAR-10.7B	47.79	74.69	55.92	44.84	55.81
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

🧩 Configuration

slices:
  - sources:
      - model: fblgit/UNA-TheBeagle-7b-v1
        layer_range: [0, 32]
      - model: argilla/distilabeled-Marcoro14-7B-slerp
        layer_range: [0, 32]
merge_method: slerp
base_model: fblgit/UNA-TheBeagle-7b-v1
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 = "mlabonne/Beagle14-7B"
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

Metric	Value
Avg.	74.76
AI2 Reasoning Challenge (25-Shot)	72.95
HellaSwag (10-Shot)	87.95
MMLU (5-Shot)	64.70
TruthfulQA (0-shot)	68.88
Winogrande (5-shot)	82.64
GSM8k (5-shot)	71.42