README.md

metadata

language:
  - en
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
model-index:
  - name: Cyrax-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=touqir/Cyrax-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: 88.19
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=touqir/Cyrax-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: 64.6
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=touqir/Cyrax-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: 77.01
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=touqir/Cyrax-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: 83.9
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=touqir/Cyrax-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: 69.22
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=touqir/Cyrax-7B
          name: Open LLM Leaderboard

Cyrax-7B

🏆 Evaluation

Open LLM Leaderboard

Model	Average	ARC	HellaSwag	MMLU	TruthfulQA	Winogrande	GSM8K
Cyrax-7B	75.98	72.95	88.19	64.6	77.01	83.9	69.22
Qwen-72B	73.6	65.19	85.94	77.37	60.19	82.48	70.43
Mixtral-8x7B-Instruct-v0.1-DPO	73.44	69.8	87.83	71.05	69.18	81.37	61.41
Mixtral-8x7B-Instruct-v0.1	72.7	70.14	87.55	71.4	64.98	81.06	61.11
llama2_70b_mmlu	68.24	65.61	87.37	71.89	49.15	82.4	52.99
falcon-180B	67.85	69.45	88.86	70.5	45.47	86.9	45.94

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "touqir/Cyrax-7B"
messages = [{"role": "user", "content": "What is Huggingface?"}]

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.	75.98
AI2 Reasoning Challenge (25-Shot)	72.95
HellaSwag (10-Shot)	88.19
MMLU (5-Shot)	64.60
TruthfulQA (0-shot)	77.01
Winogrande (5-shot)	83.90
GSM8k (5-shot)	69.22