---
widget:
- text: Hello, My name is Junpei, who are you?
  example_title: Identity
- text: Describe Aurora Borealis
  example_title: Capabilities
- text: Create a fastapi endpoint to retrieve the weather given a zip code.
  example_title: Coding
license: apache-2.0
language:
- en
pipeline_tag: text-generation
---

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "gmonsoon/delta-4b-orange"
messages = [{"role": "user", "content": "What is a large language model?"}]

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"])
```