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---
license: apache-2.0
model-index:
- name: Soniox-7B-v1.0
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: 63.91
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=soniox/Soniox-7B-v1.0
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: 82.55
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=soniox/Soniox-7B-v1.0
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: 64.38
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=soniox/Soniox-7B-v1.0
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: 53.84
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=soniox/Soniox-7B-v1.0
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: 78.06
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=soniox/Soniox-7B-v1.0
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: 56.25
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=soniox/Soniox-7B-v1.0
name: Open LLM Leaderboard
---
# Model Card for Soniox-7B-v1.0
Soniox 7B is a powerful large language model. Supports English and code with 8K context.
Matches GPT-4 performance on some benchmarks.
Built on top of Mistral 7B, enhanced with additional pre-training and fine-tuning for strong problem-solving capabilities.
Apache 2.0 License.
For more details, please read our [blog post](https://soniox.com/news/soniox-7B).
## Usage in Transformers
The model is available in transformers and can be used as follows:
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "soniox/Soniox-7B-v1.0"
model = AutoModelForCausalLM.from_pretrained(model_path, torch_dtype=torch.float16)
tokenizer = AutoTokenizer.from_pretrained(model_path)
device = "cuda"
model.to(device)
messages = [
{"role": "user", "content": "12 plus 21?"},
{"role": "assistant", "content": "33."},
{"role": "user", "content": "Five minus one?"},
]
tok_prompt = tokenizer.apply_chat_template(messages, return_tensors="pt")
model_inputs = tok_prompt.to(device)
generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
decoded = tokenizer.batch_decode(generated_ids)
print(decoded[0])
```
## Inference deployment
Refer to our [documentation](https://docs.soniox.com) for inference with vLLM and other
deployment options.
# [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_soniox__Soniox-7B-v1.0)
| Metric |Value|
|---------------------------------|----:|
|Avg. |66.50|
|AI2 Reasoning Challenge (25-Shot)|63.91|
|HellaSwag (10-Shot) |82.55|
|MMLU (5-Shot) |64.38|
|TruthfulQA (0-shot) |53.84|
|Winogrande (5-shot) |78.06|
|GSM8k (5-shot) |56.25|
|