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| import gradio as gr | |
| import os, gc, copy, torch | |
| from datetime import datetime | |
| from huggingface_hub import hf_hub_download | |
| from pynvml import * | |
| nvmlInit() | |
| gpu_h = nvmlDeviceGetHandleByIndex(0) | |
| ctx_limit = 3000 | |
| title = "RWKV-4-World-0.4B-v1-20230529-ctx4096.pth-LoRA-rwkv-19" | |
| os.environ["RWKV_JIT_ON"] = '1' | |
| os.environ["RWKV_CUDA_ON"] = '1' # if '1' then use CUDA kernel for seq mode (much faster) | |
| from rwkv.model import RWKV | |
| model_path = hf_hub_download(repo_id="hunthinn/movie_title", filename=f"{title}.pth") | |
| model = RWKV(model=model_path, strategy='cuda fp16i8 *8 -> cuda fp16') | |
| from rwkv.utils import PIPELINE, PIPELINE_ARGS | |
| pipeline = PIPELINE(model, "rwkv_vocab_v20230424") | |
| def generate_prompt(instruction, input=""): | |
| instruction = instruction.strip().replace('\r\n','\n').replace('\n\n','\n') | |
| input = input.strip().replace('\r\n','\n').replace('\n\n','\n') | |
| if input: | |
| return f"""Instruction: {instruction} | |
| Input: {input} | |
| Response:""" | |
| else: | |
| return f"""User: hi | |
| Assistant: Hi. I am your assistant and I will provide expert full response in full details. Please feel free to ask any question and I will always answer it. | |
| User: {instruction} | |
| Assistant:""" | |
| def evaluate( | |
| ctx, | |
| token_count=200, | |
| temperature=1.0, | |
| top_p=0.7, | |
| presencePenalty = 0.1, | |
| countPenalty = 0.1, | |
| ): | |
| args = PIPELINE_ARGS(temperature = max(0.2, float(temperature)), top_p = float(top_p), | |
| alpha_frequency = countPenalty, | |
| alpha_presence = presencePenalty, | |
| token_ban = [], # ban the generation of some tokens | |
| token_stop = [0]) # stop generation whenever you see any token here | |
| ctx = ctx.strip() | |
| all_tokens = [] | |
| out_last = 0 | |
| out_str = '' | |
| occurrence = {} | |
| state = None | |
| for i in range(int(token_count)): | |
| out, state = model.forward(pipeline.encode(ctx)[-ctx_limit:] if i == 0 else [token], state) | |
| for n in occurrence: | |
| out[n] -= (args.alpha_presence + occurrence[n] * args.alpha_frequency) | |
| token = pipeline.sample_logits(out, temperature=args.temperature, top_p=args.top_p) | |
| if token in args.token_stop: | |
| break | |
| all_tokens += [token] | |
| for xxx in occurrence: | |
| occurrence[xxx] *= 0.996 | |
| if token not in occurrence: | |
| occurrence[token] = 1 | |
| else: | |
| occurrence[token] += 1 | |
| tmp = pipeline.decode(all_tokens[out_last:]) | |
| if '\ufffd' not in tmp: | |
| out_str += tmp | |
| yield out_str.strip() | |
| out_last = i + 1 | |
| gpu_info = nvmlDeviceGetMemoryInfo(gpu_h) | |
| timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") | |
| print(f'{timestamp} - vram {gpu_info.total} used {gpu_info.used} free {gpu_info.free}') | |
| del out | |
| del state | |
| gc.collect() | |
| torch.cuda.empty_cache() | |
| yield out_str.strip() | |
| examples = [] | |
| ########################################################################## | |
| with gr.Blocks(title=title) as demo: | |
| gr.HTML(f"<div style=\"text-align: center;\">\n<h1>RWKV-5 World v2 - {title}</h1>\n</div>") | |
| with gr.Tab("Raw Generation"): | |
| gr.Markdown(f"This is [RWKV-5 World v2](https://huggingface.co/BlinkDL/rwkv-5-world) with 7B params - a 100% attention-free RNN [RWKV-LM](https://github.com/BlinkDL/RWKV-LM). Supports all 100+ world languages and code. And we have [200+ Github RWKV projects](https://github.com/search?o=desc&p=1&q=rwkv&s=updated&type=Repositories). *** Please try examples first (bottom of page) *** (edit them to use your question). Demo limited to ctxlen {ctx_limit}.") | |
| with gr.Row(): | |
| with gr.Column(): | |
| prompt = gr.Textbox(lines=2, label="Prompt", value="Assistant: Sure! Here is a very detailed plan to create flying pigs:") | |
| token_count = gr.Slider(10, 333, label="Max Tokens", step=10, value=333) | |
| temperature = gr.Slider(0.2, 2.0, label="Temperature", step=0.1, value=1.0) | |
| top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.3) | |
| presence_penalty = gr.Slider(0.0, 1.0, label="Presence Penalty", step=0.1, value=0) | |
| count_penalty = gr.Slider(0.0, 1.0, label="Count Penalty", step=0.1, value=1) | |
| with gr.Column(): | |
| with gr.Row(): | |
| submit = gr.Button("Submit", variant="primary") | |
| clear = gr.Button("Clear", variant="secondary") | |
| output = gr.Textbox(label="Output", lines=5) | |
| data = gr.Dataset(components=[prompt, token_count, temperature, top_p, presence_penalty, count_penalty], samples=examples, label="Example Instructions", headers=["Prompt", "Max Tokens", "Temperature", "Top P", "Presence Penalty", "Count Penalty"]) | |
| submit.click(evaluate, [prompt, token_count, temperature, top_p, presence_penalty, count_penalty], [output]) | |
| clear.click(lambda: None, [], [output]) | |
| data.click(lambda x: x, [data], [prompt, token_count, temperature, top_p, presence_penalty, count_penalty]) | |
| demo.queue(max_size=10) | |
| demo.launch(share=True) | |