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Update app.py
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app.py
CHANGED
@@ -6,40 +6,30 @@ from pynvml import *
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nvmlInit()
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gpu_h = nvmlDeviceGetHandleByIndex(0)
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ctx_limit = 1536
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title = "RWKV-4-
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os.environ["RWKV_JIT_ON"] = '1'
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os.environ["RWKV_CUDA_ON"] = '1' # if '1' then use CUDA kernel for seq mode (much faster)
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from rwkv.model import RWKV
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model_path = hf_hub_download(repo_id="BlinkDL/rwkv-4-
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model = RWKV(model=model_path, strategy='cuda fp16i8 *8 -> cuda fp16')
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# model = RWKV(model='D:/ChatRWKV/RWKV-4-Raven-7B-v9-Eng99%-Other1%-20230412-ctx8192.pth', strategy='cuda fp16i8 *10 -> cuda fp16')
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from rwkv.utils import PIPELINE, PIPELINE_ARGS
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pipeline = PIPELINE(model, "20B_tokenizer.json")
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def generate_prompt(instruction, input=None):
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instruction = instruction.strip().replace('\r\n','\n').replace('\n\n','\n')
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input = input.strip().replace('\r\n','\n').replace('\n\n','\n')
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if input:
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return f"""
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{instruction}
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{input}
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# Response:
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"""
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else:
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return f"""
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# Instruction:
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{instruction}
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"""
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def evaluate(
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instruction,
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@@ -56,8 +46,8 @@ def evaluate(
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token_ban = [], # ban the generation of some tokens
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token_stop = [0]) # stop generation whenever you see any token here
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instruction = instruction.strip().replace('\r\n','\n').replace('\n\n','\n')
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input = input.strip().replace('\r\n','\n').replace('\n\n','\n')
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ctx = generate_prompt(instruction, input)
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all_tokens = []
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@@ -243,9 +233,9 @@ def chat(
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##########################################################################
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with gr.Blocks(title=title) as demo:
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gr.HTML(f"<div style=\"text-align: center;\">\n<h1
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with gr.Tab("Instruct mode"):
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gr.Markdown(f"
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with gr.Row():
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with gr.Column():
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instruction = gr.Textbox(lines=2, label="Instruction", value="Tell me about ravens.")
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nvmlInit()
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gpu_h = nvmlDeviceGetHandleByIndex(0)
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ctx_limit = 1536
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title = "RWKV-4-World-7B-v1-OnlyForTest_84%_trained-20230618-ctx4096"
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os.environ["RWKV_JIT_ON"] = '1'
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os.environ["RWKV_CUDA_ON"] = '1' # if '1' then use CUDA kernel for seq mode (much faster)
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from rwkv.model import RWKV
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model_path = hf_hub_download(repo_id="BlinkDL/rwkv-4-world", filename=f"{title}.pth")
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model = RWKV(model=model_path, strategy='cuda fp16i8 *8 -> cuda fp16')
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from rwkv.utils import PIPELINE, PIPELINE_ARGS
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pipeline = PIPELINE(model, "20B_tokenizer.json")
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def generate_prompt(instruction, input=None):
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instruction = instruction.strip().replace('\r\n','\n').replace('\n\n','\n').replace('\n\n','\n')
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input = input.strip().replace('\r\n','\n').replace('\n\n','\n').replace('\n\n','\n')
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if input:
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return f"""Instruction: {instruction}
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Input: {input}
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Response:"""
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else:
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return f"""Question: {instruction}
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Answer:"""
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def evaluate(
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instruction,
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token_ban = [], # ban the generation of some tokens
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token_stop = [0]) # stop generation whenever you see any token here
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instruction = instruction.strip().replace('\r\n','\n').replace('\n\n','\n').replace('\n\n','\n')
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input = input.strip().replace('\r\n','\n').replace('\n\n','\n').replace('\n\n','\n')
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ctx = generate_prompt(instruction, input)
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all_tokens = []
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##########################################################################
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with gr.Blocks(title=title) as demo:
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gr.HTML(f"<div style=\"text-align: center;\">\n<h1>🌍World - {title}</h1>\n</div>")
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with gr.Tab("Instruct mode"):
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gr.Markdown(f"World is [RWKV 7B](https://github.com/BlinkDL/ChatRWKV) 100% RNN [RWKV-LM](https://github.com/BlinkDL/RWKV-LM) trained on 100+ world languages. *** Please try examples first (bottom of page) *** (edit them to use your question). Demo limited to ctxlen {ctx_limit}. Finetuned on alpaca, gpt4all, codealpaca and more. For best results, *** keep you prompt short and clear ***.</b>.") # <b>UPDATE: now with Chat (see above, as a tab) ==> turn off as of now due to VRAM leak caused by buggy code.
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with gr.Row():
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with gr.Column():
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instruction = gr.Textbox(lines=2, label="Instruction", value="Tell me about ravens.")
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