README.md

---
language:
- en
datasets: 
- kyujinpy/Open-platypus-Commercial
library_name: transformers
pipeline_tag: text-generation
license: mit
---

# **phi-2-platypus-Commercial-lora**  

## Model Details   
**Model Developers**  
- field2437

**Base Model**   
- microsoft/phi-2(https://huggingface.co/microsoft/phi-2)   

**Training Dataset**   
- kyujinpy/Open-platypus-Commercial(https://huggingface.co/datasets/kyujinpy/Open-platypus-Commercial)  

  
---  
# Model comparisons1
> AI-Harness evaluation; [link](https://github.com/EleutherAI/lm-evaluation-harness)   
   
| Model | Copa | HellaSwag | BoolQ | MMLU |
| --- | --- | --- | --- | --- |
|  | 0-shot | 0-shot | 0-shot | 0-shot |
| **phi-2-platypus-Commercial-lora** | 0.8900 | 0.5573 | 0.8260 | 0.5513 |
  
---
# Sample Code
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

torch.set_default_device("cuda")

model = AutoModelForCausalLM.from_pretrained("field2437/phi-2-platypus-Commercial-lora", torch_dtype="auto", trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("field2437/phi-2-platypus-Commercial-lora", trust_remote_code=True)

inputs = tokenizer('''Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
Let $f(x)$ be the polynomial \\[f(x)=3x^4+5x^2-9x-2.\\] If $g(x)$ is equal to the polynomial $f(x-1)$, what is the sum of the coefficients of $g$?

### Response:
''', return_tensors="pt", return_attention_mask=False)

outputs = model.generate(**inputs, max_length=200)
text = tokenizer.batch_decode(outputs)[0]
print(text)
```

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