import gradio as gr import os, gc, copy, torch from datetime import datetime from huggingface_hub import hf_hub_download from pynvml import * # Flag to check if GPU is present HAS_GPU = False # Model title and context size limit ctx_limit = 2000 title = "RWKV-5-World-1B5-v2-20231025-ctx4096" model_file = "rwkv-5-h-world-1b5" # Get the GPU count try: nvmlInit() GPU_COUNT = nvmlDeviceGetCount() if GPU_COUNT > 0: HAS_GPU = True gpu_h = nvmlDeviceGetHandleByIndex(0) except NVMLError as error: print(error) os.environ["RWKV_JIT_ON"] = '1' # Model strat to use MODEL_STRAT="cpu bf16" os.environ["RWKV_CUDA_ON"] = '0' # if '1' then use CUDA kernel for seq mode (much faster) # Switch to GPU mode if HAS_GPU == True : os.environ["RWKV_CUDA_ON"] = '1' MODEL_STRAT = "cuda bf16" # Load the model accordingly from rwkv.model import RWKV model_path = hf_hub_download(repo_id="a686d380/rwkv-5-h-world", filename=f"{model_file}.pth") model = RWKV(model=model_path, strategy=MODEL_STRAT) from rwkv.utils import PIPELINE, PIPELINE_ARGS pipeline = PIPELINE(model, "rwkv_vocab_v20230424") # Prompt generation 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:""" # Evaluation logic def evaluate( ctx, token_count=200, temperature=1.0, top_p=0.7, presencePenalty = 0.1, countPenalty = 0.1, ): print(ctx) 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 if HAS_GPU == True : gpu_info = nvmlDeviceGetMemoryInfo(gpu_h) print(f'vram {gpu_info.total} used {gpu_info.used} free {gpu_info.free}') del out del state gc.collect() if HAS_GPU == True : torch.cuda.empty_cache() yield out_str.strip() ########################################################################## # Gradio blocks with gr.Blocks(title=title) as demo: gr.HTML(f"
\n

RWKV-5 World v2 - {title}

\n
") with gr.Tab("Raw Generation"): gr.Markdown(f"This is RWKV-5 World v2 with 1.5B 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="裸体少女") token_count = gr.Slider(10, 300, label="Max Tokens", step=10, value=200) 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=1) 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], 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]) # Gradio launch demo.queue(concurrency_count=1, max_size=10) demo.launch(share=False)