Delete alpacatest.py

alpacatest.py

@@ -1,64 +0,0 @@
-from datasets import load_dataset
-from transformers import RwkvForCausalLM, GPTNeoXTokenizerFast,GPT2Config,pipeline,GenerationConfig
-import torch
-import numpy as np
-import gradio as gr
-
-if torch.cuda.is_available():
-    device = "cuda"
-else:
-    device = "cpu"
-
-model = RwkvForCausalLM.from_pretrained("rwkv-alpaca") 
-model = model.to(device)
-
-tokenizer = GPTNeoXTokenizerFast.from_pretrained("rwkv-alpaca", add_special_tokens=True)
-
-
-
-#rwkv with alpaca 
-def generate_prompt(instruction, input=None):
-    
-    return f"""Below is an instruction that describes a task. Write a response that appropriately completes the request.
-
-### Instruction:
-{instruction}
-
-### Response:"""
-
-def evaluate(
-    instruction,
-    temperature=0.1,
-    top_p=0.75,
-    top_k=40,
-    max_new_tokens=128,
-):
-    prompt = generate_prompt(instruction)
-    input_ids = tokenizer.encode(prompt, return_tensors='pt').to(device)
-    out = model.generate(input_ids=input_ids,temperature=temperature,top_p=top_p,top_k=top_k,max_new_tokens=max_new_tokens)
-    answer = tokenizer.decode(out[0])
-    return answer.split("### Response:")[1].strip()
-
-
-gr.Interface(
-    fn=evaluate,#接口函数
-    inputs=[
-        gr.components.Textbox(
-            lines=2, label="Instruction", placeholder="Tell me about alpacas."
-        ),
-        gr.components.Slider(minimum=0, maximum=1, value=0.1, label="Temperature"),
-        gr.components.Slider(minimum=0, maximum=1, value=0.75, label="Top p"),
-        gr.components.Slider(minimum=0, maximum=100, step=1, value=40, label="Top k"),
-        gr.components.Slider(
-            minimum=1, maximum=2000, step=1, value=128, label="Max tokens"
-        ),
-    ],
-    outputs=[
-        gr.inputs.Textbox(
-            lines=5,
-            label="Output",
-        )
-    ],
-    title="RWKV-Alpaca",
-    description="RWKV,easy in HF.",
-).launch()