README.md

---
license: cc-by-nc-4.0
---

Discription 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))
```