---
library_name: peft
base_model: tiiuae/falcon-7b
---

### Direct Use

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

model = "Dhruvil47/falcon-7b-bioarxiv-qa"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    tokenizer=tokenizer,
    torch_dtype=torch.bfloat16,
    trust_remote_code=True,
    device_map="auto",
)


input_prompt = "Question: Are group 2 innate lymphoid cells ( ILC2s ) increased in chronic rhinosinusitis with nasal polyps or eosinophilia?\nAnswer:"

sequences = pipeline(
    input_prompt,
    max_length=300,
    do_sample=True,
    top_k=10,
    num_return_sequences=1,
    eos_token_id=tokenizer.eos_token_id,
)

for seq in sequences:
    generated_text = seq['generated_text'].split("\nQuestion:")[0]
    generated_text = generated_text.replace(input_prompt, "").strip()
    print(generated_text)

```