README.md

---
license: cc-by-nc-4.0
model-index:
- name: SOLAR-10.7B-dpo-instruct-tuned-v0.1
  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: 65.19
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=pinkyponky/SOLAR-10.7B-dpo-instruct-tuned-v0.1
      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: 86.09
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=pinkyponky/SOLAR-10.7B-dpo-instruct-tuned-v0.1
      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: 66.25
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=pinkyponky/SOLAR-10.7B-dpo-instruct-tuned-v0.1
      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: 51.81
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=pinkyponky/SOLAR-10.7B-dpo-instruct-tuned-v0.1
      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: 83.98
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=pinkyponky/SOLAR-10.7B-dpo-instruct-tuned-v0.1
      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: 58.76
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=pinkyponky/SOLAR-10.7B-dpo-instruct-tuned-v0.1
      name: Open LLM Leaderboard
---

Description to load and test will be added soon. More details on training and data will be added aswell.


### **Loading the Model**

Use the following Python code to load the model:

```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("pinkyponky/SOLAR-10.7B-dpo-instruct-tuned-v0.1")
model = AutoModelForCausalLM.from_pretrained(
    "Upstage/SOLAR-10.7B-v1.0",
    device_map="auto",
    torch_dtype=torch.bfloat16,
)
```

### **Generating Text**

To generate text, use the following Python code:

```python
text = "Hi, my name is "
inputs = tokenizer(text, return_tensors="pt")

outputs = model.generate(**inputs, max_new_tokens=64)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
# [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_pinkyponky__SOLAR-10.7B-dpo-instruct-tuned-v0.1)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |68.68|
|AI2 Reasoning Challenge (25-Shot)|65.19|
|HellaSwag (10-Shot)              |86.09|
|MMLU (5-Shot)                    |66.25|
|TruthfulQA (0-shot)              |51.81|
|Winogrande (5-shot)              |83.98|
|GSM8k (5-shot)                   |58.76|