Cyrax-7B / README.md
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---
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**](https://huggingface.co/touqir/Cyrax-7B)| **75.98**| **72.95**| 88.19| 64.6| **77.01**| 83.9| **69.22** |
|[Qwen-72B](https://huggingface.co/Qwen/Qwen-72B)| 73.6| 65.19| 85.94| **77.37**| 60.19| 82.48| 70.43|
|[Mixtral-8x7B-Instruct-v0.1-DPO](https://huggingface.co/cloudyu/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](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1)| 72.7| 70.14 | 87.55| 71.4| 64.98| 81.06| 61.11 |
|[llama2_70b_mmlu](https://huggingface.co/itsliupeng/llama2_70b_mmlu)| 68.24| 65.61| 87.37| 71.89| 49.15| 82.4| 52.99 |
|[falcon-180B](https://huggingface.co/tiiuae/falcon-180B)| 67.85| 69.45| **88.86**| 70.5| 45.47| **86.9**| 45.94|
## 💻 Usage
```python
!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](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_touqir__Cyrax-7B)
| 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|