---
language:
- en
license: apache-2.0
model-index:
- name: Mixtral-GQA-400m-v2
  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: 20.22
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/Mixtral-GQA-400m-v2
      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: 27.78
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/Mixtral-GQA-400m-v2
      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: 26.1
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/Mixtral-GQA-400m-v2
      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: 46.55
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/Mixtral-GQA-400m-v2
      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: 49.96
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/Mixtral-GQA-400m-v2
      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: 0.08
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/Mixtral-GQA-400m-v2
      name: Open LLM Leaderboard
---



#  BEE-spoke-data/Mixtral-GQA-400m-v2




## testing code

```python
# !pip install -U -q transformers datasets accelerate sentencepiece
import pprint as pp
from transformers import pipeline

pipe = pipeline(
    "text-generation",
    model="BEE-spoke-data/Mixtral-GQA-400m-v2",
    device_map="auto",
)
pipe.model.config.pad_token_id = pipe.model.config.eos_token_id

prompt = "My favorite movie is Godfather because"

res = pipe(
    prompt,
    max_new_tokens=256,
    top_k=4,
    penalty_alpha=0.6,
    use_cache=True,
    no_repeat_ngram_size=4,
    repetition_penalty=1.1,
    renormalize_logits=True,
)
pp.pprint(res[0])
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_BEE-spoke-data__Mixtral-GQA-400m-v2)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |28.45|
|AI2 Reasoning Challenge (25-Shot)|20.22|
|HellaSwag (10-Shot)              |27.78|
|MMLU (5-Shot)                    |26.10|
|TruthfulQA (0-shot)              |46.55|
|Winogrande (5-shot)              |49.96|
|GSM8k (5-shot)                   | 0.08|