| import torch |
| import gradio as gr |
| from transformers import AutoModelForCausalLM, AutoTokenizer, StoppingCriteria, StoppingCriteriaList |
|
|
| tokenizer = AutoTokenizer.from_pretrained("stabilityai/stablelm-tuned-alpha-7b") |
| model = AutoModelForCausalLM.from_pretrained("stabilityai/stablelm-tuned-alpha-7b") |
| model.half().cuda() |
|
|
| class StopOnTokens(StoppingCriteria): |
| def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs) -> bool: |
| stop_ids = [50278, 50279, 50277, 1, 0] |
| for stop_id in stop_ids: |
| if input_ids[0][-1] == stop_id: |
| return True |
| return False |
|
|
| system_prompt = """<|SYSTEM|># StableLM Tuned (Alpha version) |
| - StableLM is a helpful and harmless open-source AI language model developed by StabilityAI. |
| - StableLM is excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user. |
| - StableLM is more than just an information source, StableLM is also able to write poetry, short stories, and make jokes. |
| - StableLM will refuse to participate in anything that could harm a human. |
| """ |
|
|
| prompt = f"{system_prompt}<|USER|>What's your mood today?<|ASSISTANT|>" |
|
|
| inputs = tokenizer(prompt, return_tensors="pt").to("cuda") |
| tokens = model.generate( |
| **inputs, |
| max_new_tokens=64, |
| temperature=0.7, |
| do_sample=True, |
| stopping_criteria=StoppingCriteriaList([StopOnTokens()]) |
| ) |
|
|
|
|
| print(tokenizer.decode(tokens[0], skip_special_tokens=True)) |
