Duplicate from Luigi/Taiwan-LLaMa-13b-v1.0-chat.ggmlv3

Co-authored-by: Luigi LIU <[email protected]>

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
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+*.lfs.* filter=lfs diff=lfs merge=lfs -text
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+*.model filter=lfs diff=lfs merge=lfs -text
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LICENSE.txt

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+LLAMA 2 COMMUNITY LICENSE AGREEMENT	
+Llama 2 Version Release Date: July 18, 2023
+
+"Agreement" means the terms and conditions for use, reproduction, distribution and 
+modification of the Llama Materials set forth herein.
+
+"Documentation" means the specifications, manuals and documentation 
+accompanying Llama 2 distributed by Meta at ai.meta.com/resources/models-and-
+libraries/llama-downloads/.
+
+"Licensee" or "you" means you, or your employer or any other person or entity (if 
+you are entering into this Agreement on such person or entity's behalf), of the age 
+required under applicable laws, rules or regulations to provide legal consent and that 
+has legal authority to bind your employer or such other person or entity if you are 
+entering in this Agreement on their behalf.
+
+"Llama 2" means the foundational large language models and software and 
+algorithms, including machine-learning model code, trained model weights, 
+inference-enabling code, training-enabling code, fine-tuning enabling code and other 
+elements of the foregoing distributed by Meta at ai.meta.com/resources/models-and-
+libraries/llama-downloads/.
+
+"Llama Materials" means, collectively, Meta's proprietary Llama 2 and 
+Documentation (and any portion thereof) made available under this Agreement.
+
+"Meta" or "we" means Meta Platforms Ireland Limited (if you are located in or, if you 
+are an entity, your principal place of business is in the EEA or Switzerland) and Meta 
+Platforms, Inc. (if you are located outside of the EEA or Switzerland). 
+
+By clicking "I Accept" below or by using or distributing any portion or element of the 
+Llama Materials, you agree to be bound by this Agreement.
+
+1. License Rights and Redistribution. 
+
+      a. Grant of Rights. You are granted a non-exclusive, worldwide, non-
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+      
+      b. Redistribution and Use.  
+
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+
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+
+            iv. Your use of the Llama Materials must comply with applicable laws 
+and regulations (including trade compliance laws and regulations) and adhere to the 
+Acceptable Use Policy for the Llama Materials (available at 
+https://ai.meta.com/llama/use-policy), which is hereby incorporated by reference into 
+this Agreement.
+
+            v. You will not use the Llama Materials or any output or results of the 
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+derivative works thereof).  
+
+2. Additional Commercial Terms. If, on the Llama 2 version release date, the 
+monthly active users of the products or services made available by or for Licensee, 
+or Licensee's affiliates, is greater than 700 million monthly active users in the 
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+5. Intellectual Property.
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+does not apply to this Agreement. The courts of California shall have exclusive 
+jurisdiction of any dispute arising out of this Agreement. 
+

README.md

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+---
+title: llama-2-13b-chat.ggmlv3.q4_K_S
+emoji: 🏆
+colorFrom: purple
+colorTo: gray
+sdk: gradio
+sdk_version: 3.37.0
+app_file: app.py
+pinned: false
+suggested_hardware: a10g-small
+duplicated_from: Luigi/Taiwan-LLaMa-13b-v1.0-chat.ggmlv3
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# LLAMA v2 Models
+
+Llama v2 was introduced in [this paper](https://arxiv.org/abs/2307.09288).
+
+This Space demonstrates [Llama-2-7b-chat-hf](https://huggingface.co/spaces/huggingface-projects/llama-2-13b-chat/blob/main/meta-llama/Llama-2-7b-chat-hf) from Meta. Please, check the original model card for details.
+
+

USE_POLICY.md

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+# Llama 2 Acceptable Use Policy
+
+Meta is committed to promoting safe and fair use of its tools and features, including Llama 2. If you access or use Llama 2, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of this policy can be found at [ai.meta.com/llama/use-policy](http://ai.meta.com/llama/use-policy).
+
+## Prohibited Uses
+We want everyone to use Llama 2 safely and responsibly. You agree you will not use, or allow others to use, Llama 2 to: 
+
+1. Violate the law or others’ rights, including to:
+    1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as: 
+        1. Violence or terrorism 
+        2. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material
+        3. Human trafficking, exploitation, and sexual violence
+        4. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.
+        5. Sexual solicitation
+        6. Any other criminal activity
+    2. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals
+    3. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services
+    4. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices 
+    5. Collect, process, disclose, generate, or infer health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws
+    6. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama 2 Materials
+    7. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system 
+
+
+
+2. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Llama 2 related to the following:
+    1. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State
+    2. Guns and illegal weapons (including weapon development)
+    3. Illegal drugs and regulated/controlled substances
+    4. Operation of critical infrastructure, transportation technologies, or heavy machinery
+    5. Self-harm or harm to others, including suicide, cutting, and eating disorders
+    6. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual
+
+
+
+3. Intentionally deceive or mislead others, including use of Llama 2 related to the following:
+    1. Generating, promoting, or furthering fraud or the creation or promotion of disinformation
+    2. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content
+    3. Generating, promoting, or further distributing spam
+    4. Impersonating another individual without consent, authorization, or legal right
+    5. Representing that the use of Llama 2 or outputs are human-generated
+    6. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement 
+4. Fail to appropriately disclose to end users any known dangers of your AI system 
+
+Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation of this Policy through one of the following means:
+
+* Reporting issues with the model: [github.com/facebookresearch/llama](http://github.com/facebookresearch/llama)
+* Reporting risky content generated by the model: [developers.facebook.com/llama_output_feedback](http://developers.facebook.com/llama_output_feedback)
+* Reporting bugs and security concerns: [facebook.com/whitehat/info](http://facebook.com/whitehat/info)
+* Reporting violations of the Acceptable Use Policy or unlicensed uses of Llama: [[email protected]](mailto:[email protected])
+

app.py

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+from typing import Iterator
+
+import gradio as gr
+import torch
+
+from model import get_input_token_length, run
+
+DEFAULT_SYSTEM_PROMPT = """A chat between a curious user and a AI telephone assistant. The assistant gives helpful answers in less than 30 tokens to the user's questions. You are built by NTU Miulab by Yen-Ting Lin for research purpose."""
+MAX_MAX_NEW_TOKENS = 2048
+DEFAULT_MAX_NEW_TOKENS = 1024
+MAX_INPUT_TOKEN_LENGTH = 4000
+
+DESCRIPTION = """
+# Taiwan-LLaMa-13b-1.0.ggmlv3
+"""
+
+LICENSE = """
+<p/>
+
+---
+[Llama-2-13b-chat](https://huggingface.co/meta-llama/Llama-2-13b-chat) by Meta).
+"""
+
+if not torch.cuda.is_available():
+    DESCRIPTION += '\n<p>Running on CPU 🥶 This demo does not work on GPU.</p>'
+
+def clear_and_save_textbox(message: str) -> tuple[str, str]:
+    return '', message
+
+
+def display_input(message: str,
+                  history: list[tuple[str, str]]) -> list[tuple[str, str]]:
+    history.append((message, ''))
+    return history
+
+
+def delete_prev_fn(
+        history: list[tuple[str, str]]) -> tuple[list[tuple[str, str]], str]:
+    try:
+        message, _ = history.pop()
+    except IndexError:
+        message = ''
+    return history, message or ''
+
+
+def generate(
+    message: str,
+    history_with_input: list[tuple[str, str]],
+    system_prompt: str,
+    max_new_tokens: int,
+    temperature: float,
+    top_p: float,
+    top_k: int,
+) -> Iterator[list[tuple[str, str]]]:
+    if max_new_tokens > MAX_MAX_NEW_TOKENS:
+        raise ValueError
+
+    history = history_with_input[:-1]
+    generator = run(message, history, system_prompt, max_new_tokens, temperature, top_p, top_k)
+    try:
+        first_response = next(generator)
+        yield history + [(message, first_response)]
+    except StopIteration:
+        yield history + [(message, '')]
+    for response in generator:
+        yield history + [(message, response)]
+
+
+def process_example(message: str) -> tuple[str, list[tuple[str, str]]]:
+    generator = generate(message, [], DEFAULT_SYSTEM_PROMPT, 1024, 1, 0.95, 50)
+    for x in generator:
+        pass
+    return '', x
+
+
+def check_input_token_length(message: str, chat_history: list[tuple[str, str]], system_prompt: str) -> None:
+    input_token_length = get_input_token_length(message, chat_history, system_prompt)
+    if input_token_length > MAX_INPUT_TOKEN_LENGTH:
+        raise gr.Error(f'The accumulated input is too long ({input_token_length} > {MAX_INPUT_TOKEN_LENGTH}). Clear your chat history and try again.')
+
+
+with gr.Blocks(css='style.css') as demo:
+    gr.Markdown(DESCRIPTION)
+    gr.DuplicateButton(value='Duplicate Space for private use',
+                       elem_id='duplicate-button')
+
+    with gr.Group():
+        chatbot = gr.Chatbot(label='Chatbot')
+        with gr.Row():
+            textbox = gr.Textbox(
+                container=False,
+                show_label=False,
+                placeholder='Type a message...',
+                scale=10,
+            )
+            submit_button = gr.Button('Submit',
+                                      variant='primary',
+                                      scale=1,
+                                      min_width=0)
+    with gr.Row():
+        retry_button = gr.Button('🔄  Retry', variant='secondary')
+        undo_button = gr.Button('↩️ Undo', variant='secondary')
+        clear_button = gr.Button('🗑️  Clear', variant='secondary')
+
+    saved_input = gr.State()
+
+    with gr.Accordion(label='Advanced options', open=False):
+        system_prompt = gr.Textbox(label='System prompt',
+                                   value=DEFAULT_SYSTEM_PROMPT,
+                                   lines=6)
+        max_new_tokens = gr.Slider(
+            label='Max new tokens',
+            minimum=1,
+            maximum=MAX_MAX_NEW_TOKENS,
+            step=1,
+            value=DEFAULT_MAX_NEW_TOKENS,
+        )
+        temperature = gr.Slider(
+            label='Temperature',
+            minimum=0.1,
+            maximum=4.0,
+            step=0.1,
+            value=0.1,
+        )
+        top_p = gr.Slider(
+            label='Top-p (nucleus sampling)',
+            minimum=0.05,
+            maximum=1.0,
+            step=0.05,
+            value=0.9,
+        )
+        top_k = gr.Slider(
+            label='Top-k',
+            minimum=1,
+            maximum=1000,
+            step=1,
+            value=50,
+        )
+
+    gr.Examples(
+        examples=[
+            '以惡地景觀著名的是高雄哪一個景點?',
+            '唐鳳是誰？',
+            'NTU 在哪?',
+            '甚麼是22K?',
+            '肉圓要不要加香菜？',
+        ],
+        inputs=textbox,
+        outputs=[textbox, chatbot],
+        fn=process_example,
+        cache_examples=True,
+    )
+
+    gr.Markdown(LICENSE)
+
+    textbox.submit(
+        fn=clear_and_save_textbox,
+        inputs=textbox,
+        outputs=[textbox, saved_input],
+        api_name=False,
+        queue=False,
+    ).then(
+        fn=display_input,
+        inputs=[saved_input, chatbot],
+        outputs=chatbot,
+        api_name=False,
+        queue=False,
+    ).then(
+        fn=check_input_token_length,
+        inputs=[saved_input, chatbot, system_prompt],
+        api_name=False,
+        queue=False,
+    ).success(
+        fn=generate,
+        inputs=[
+            saved_input,
+            chatbot,
+            system_prompt,
+            max_new_tokens,
+            temperature,
+            top_p,
+            top_k,
+        ],
+        outputs=chatbot,
+        api_name=False,
+    )
+
+    button_event_preprocess = submit_button.click(
+        fn=clear_and_save_textbox,
+        inputs=textbox,
+        outputs=[textbox, saved_input],
+        api_name="submit",
+#        api_name=False,
+        queue=False,
+    ).then(
+        fn=display_input,
+        inputs=[saved_input, chatbot],
+        outputs=chatbot,
+        api_name=False,
+        queue=False,
+    ).then(
+        fn=check_input_token_length,
+        inputs=[saved_input, chatbot, system_prompt],
+        api_name=False,
+        queue=False,
+    ).success(
+        fn=generate,
+        inputs=[
+            saved_input,
+            chatbot,
+            system_prompt,
+            max_new_tokens,
+            temperature,
+            top_p,
+            top_k,
+        ],
+        outputs=chatbot,
+        api_name=False,
+    )
+
+    retry_button.click(
+        fn=delete_prev_fn,
+        inputs=chatbot,
+        outputs=[chatbot, saved_input],
+        api_name=False,
+        queue=False,
+    ).then(
+        fn=display_input,
+        inputs=[saved_input, chatbot],
+        outputs=chatbot,
+        api_name=False,
+        queue=False,
+    ).then(
+        fn=generate,
+        inputs=[
+            saved_input,
+            chatbot,
+            system_prompt,
+            max_new_tokens,
+            temperature,
+            top_p,
+            top_k,
+        ],
+        outputs=chatbot,
+        api_name=False,
+    )
+
+    undo_button.click(
+
+        fn=delete_prev_fn,
+        inputs=chatbot,
+        outputs=[chatbot, saved_input],
+        api_name=False,
+        queue=False,
+    ).then(
+        fn=lambda x: x,
+        inputs=[saved_input],
+        outputs=textbox,
+        api_name=False,
+        queue=False,
+    )
+
+    clear_button.click(
+        fn=lambda: ([], ''),
+        outputs=[chatbot, saved_input],
+        queue=False,
+        api_name=False,
+    )
+
+demo.queue(max_size=20).launch()

conversation.py

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+# Cloned from 
+# https://huggingface.co/spaces/yentinglin/Taiwan-LLaMa2/raw/main/conversation.py
+
+"""
+Conversation prompt template.
+Now we support
+- Vicuna
+- Koala
+- OpenAssistant/oasst-sft-1-pythia-12b
+- StabilityAI/stablelm-tuned-alpha-7b
+- databricks/dolly-v2-12b
+- THUDM/chatglm-6b
+- Alpaca/LLaMa
+"""
+
+import dataclasses
+from enum import auto, Enum
+from typing import List, Tuple, Any
+
+
+class SeparatorStyle(Enum):
+    """Different separator style."""
+
+    SINGLE = auto()
+    TWO = auto()
+    DOLLY = auto()
+    OASST_PYTHIA = auto()
+
+
+@dataclasses.dataclass
+class Conversation:
+    """A class that keeps all conversation history."""
+
+    system: str
+    roles: List[str]
+    messages: List[List[str]]
+    offset: int
+    sep_style: SeparatorStyle = SeparatorStyle.SINGLE
+    sep: str = "###"
+    sep2: str = None
+
+    # Used for gradio server
+    skip_next: bool = False
+    conv_id: Any = None
+
+    def get_prompt(self):
+        if self.sep_style == SeparatorStyle.SINGLE:
+            ret = self.system
+            for role, message in self.messages:
+                if message:
+                    ret += self.sep + " " + role + ": " + message
+                else:
+                    ret += self.sep + " " + role + ":"
+            return ret
+        elif self.sep_style == SeparatorStyle.TWO:
+            seps = [self.sep, self.sep2]
+            ret = self.system + seps[0]
+            for i, (role, message) in enumerate(self.messages):
+                if message:
+                    ret += role + ": " + message + seps[i % 2]
+                else:
+                    ret += role + ":"
+            return ret
+        elif self.sep_style == SeparatorStyle.DOLLY:
+            seps = [self.sep, self.sep2]
+            ret = self.system
+            for i, (role, message) in enumerate(self.messages):
+                if message:
+                    ret += role + ":\n" + message + seps[i % 2]
+                    if i % 2 == 1:
+                        ret += "\n\n"
+                else:
+                    ret += role + ":\n"
+            return ret
+        elif self.sep_style == SeparatorStyle.OASST_PYTHIA:
+            ret = self.system
+            for role, message in self.messages:
+                if message:
+                    ret += role + message + self.sep
+                else:
+                    ret += role
+            return ret
+        else:
+            raise ValueError(f"Invalid style: {self.sep_style}")
+
+    def append_message(self, role, message):
+        self.messages.append([role, message])
+
+    def to_gradio_chatbot(self):
+        ret = []
+        for i, (role, msg) in enumerate(self.messages[self.offset :]):
+            if i % 2 == 0:
+                ret.append([msg, None])
+            else:
+                ret[-1][-1] = msg
+        return ret
+
+    def copy(self):
+        return Conversation(
+            system=self.system,
+            roles=self.roles,
+            messages=[[x, y] for x, y in self.messages],
+            offset=self.offset,
+            sep_style=self.sep_style,
+            sep=self.sep,
+            sep2=self.sep2,
+            conv_id=self.conv_id,
+        )
+
+    def dict(self):
+        return {
+            "system": self.system,
+            "roles": self.roles,
+            "messages": self.messages,
+            "offset": self.offset,
+            "sep": self.sep,
+            "sep2": self.sep2,
+            "conv_id": self.conv_id,
+        }
+
+
+conv_one_shot = Conversation(
+    system="A chat between a curious human and an artificial intelligence assistant. "
+    "The assistant gives helpful, detailed, and polite answers to the human's questions.",
+    roles=("Human", "Assistant"),
+    messages=(
+        (
+            "Human",
+            "What are the key differences between renewable and non-renewable energy sources?",
+        ),
+        (
+            "Assistant",
+            "Renewable energy sources are those that can be replenished naturally in a relatively "
+            "short amount of time, such as solar, wind, hydro, geothermal, and biomass. "
+            "Non-renewable energy sources, on the other hand, are finite and will eventually be "
+            "depleted, such as coal, oil, and natural gas. Here are some key differences between "
+            "renewable and non-renewable energy sources:\n"
+            "1. Availability: Renewable energy sources are virtually inexhaustible, while non-renewable "
+            "energy sources are finite and will eventually run out.\n"
+            "2. Environmental impact: Renewable energy sources have a much lower environmental impact "
+            "than non-renewable sources, which can lead to air and water pollution, greenhouse gas emissions, "
+            "and other negative effects.\n"
+            "3. Cost: Renewable energy sources can be more expensive to initially set up, but they typically "
+            "have lower operational costs than non-renewable sources.\n"
+            "4. Reliability: Renewable energy sources are often more reliable and can be used in more remote "
+            "locations than non-renewable sources.\n"
+            "5. Flexibility: Renewable energy sources are often more flexible and can be adapted to different "
+            "situations and needs, while non-renewable sources are more rigid and inflexible.\n"
+            "6. Sustainability: Renewable energy sources are more sustainable over the long term, while "
+            "non-renewable sources are not, and their depletion can lead to economic and social instability.",
+        ),
+    ),
+    offset=2,
+    sep_style=SeparatorStyle.SINGLE,
+    sep="###",
+)
+
+
+conv_vicuna_v1_1 = Conversation(
+    system="A chat between a curious user and an artificial intelligence assistant. "
+    "The assistant gives helpful, detailed, and polite answers to the user's questions. You are built by NTU Miulab by Yen-Ting Lin for research purpose.",
+    # system="一位好奇的用戶和一個人工智能助理之間的聊天。你是一位助理。請對用戶的問題提供有用、詳細和有禮貌的答案。",
+    roles=("USER", "ASSISTANT"),
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.TWO,
+    sep=" ",
+    sep2="</s>",
+)
+
+conv_story = Conversation(
+    system="A chat between a curious user and an artificial intelligence assistant. "
+    "The assistant gives helpful, detailed, and polite answers to the user's questions.",
+    roles=("USER", "ASSISTANT"),
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.TWO,
+    sep=" ",
+    sep2="<|endoftext|>",
+)
+
+conv_koala_v1 = Conversation(
+    system="BEGINNING OF CONVERSATION:",
+    roles=("USER", "GPT"),
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.TWO,
+    sep=" ",
+    sep2="</s>",
+)
+
+conv_dolly = Conversation(
+    system="Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n",
+    roles=("### Instruction", "### Response"),
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.DOLLY,
+    sep="\n\n",
+    sep2="### End",
+)
+
+conv_oasst = Conversation(
+    system="",
+    roles=("<|prompter|>", "<|assistant|>"),
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.OASST_PYTHIA,
+    sep="<|endoftext|>",
+)
+
+conv_stablelm = Conversation(
+    system="""<|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.
+""",
+    roles=("<|USER|>", "<|ASSISTANT|>"),
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.OASST_PYTHIA,
+    sep="",
+)
+
+conv_templates = {
+    "conv_one_shot": conv_one_shot,
+    "vicuna_v1.1": conv_vicuna_v1_1,
+    "koala_v1": conv_koala_v1,
+    "dolly": conv_dolly,
+    "oasst": conv_oasst,
+}
+
+
+def get_default_conv_template(model_name):
+    model_name = model_name.lower()
+    if "vicuna" in model_name or "output" in model_name:
+        return conv_vicuna_v1_1
+    elif "koala" in model_name:
+        return conv_koala_v1
+    elif "dolly-v2" in model_name:
+        return conv_dolly
+    elif "oasst" in model_name and "pythia" in model_name:
+        return conv_oasst
+    elif "stablelm" in model_name:
+        return conv_stablelm
+    return conv_one_shot
+
+
+def compute_skip_echo_len(model_name, conv, prompt):
+    model_name = model_name.lower()
+    if "chatglm" in model_name:
+        skip_echo_len = len(conv.messages[-2][1]) + 1
+    elif "dolly-v2" in model_name:
+        special_toks = ["### Instruction:", "### Response:", "### End"]
+        skip_echo_len = len(prompt)
+        for tok in special_toks:
+            skip_echo_len -= prompt.count(tok) * len(tok)
+    elif "oasst" in model_name and "pythia" in model_name:
+        special_toks = ["<|prompter|>", "<|assistant|>", "<|endoftext|>"]
+        skip_echo_len = len(prompt)
+        for tok in special_toks:
+            skip_echo_len -= prompt.count(tok) * len(tok)
+    elif "stablelm" in model_name:
+        special_toks = ["<|SYSTEM|>", "<|USER|>", "<|ASSISTANT|>"]
+        skip_echo_len = len(prompt)
+        for tok in special_toks:
+            skip_echo_len -= prompt.count(tok) * len(tok)
+    else:
+        skip_echo_len = len(prompt) + 1 - prompt.count("</s>") * 3
+    return skip_echo_len
+
+
+if __name__ == "__main__":
+    print(default_conversation.get_prompt())

model.py

@@ -0,0 +1,72 @@
+from typing import Iterator
+from llama_cpp import Llama
+from huggingface_hub import hf_hub_download
+from conversation import get_default_conv_template
+
+def download_model():
+    # See https://github.com/OpenAccess-AI-Collective/ggml-webui/blob/main/tabbed.py
+    # https://huggingface.co/spaces/kat33/llama.cpp/blob/main/app.py
+    print(f"Downloading model: {model_repo}/{model_filename}")
+    file = hf_hub_download(
+            repo_id=model_repo, filename=model_filename
+    )
+    print("Downloaded " + file)
+    return file
+
+model_repo = "audreyt/Taiwan-LLaMa-v1.0-GGML"
+model_filename = "Taiwan-LLaMa-13b-1.0.ggmlv3.q4_K_S.bin"
+# model_filename = "Chinese-Llama-2-7b.ggmlv3.q8_0.bin"
+model_path = download_model()
+
+# load Llama-2
+llm = Llama(model_path=model_path, n_ctx=4000, verbose=False)
+
+
+def get_prompt(message: str, chat_history: list[tuple[str, str]],
+               system_prompt: str) -> str:
+
+    # Modified from 
+    # https://huggingface.co/spaces/yentinglin/Taiwan-LLaMa2/blob/main/app.py
+                   
+    conv = get_default_conv_template("vicuna").copy()
+    roles = {"human": conv.roles[0], "gpt": conv.roles[1]}  # map human to USER and gpt to ASSISTANT
+    conv.system = system_prompt
+    for user, bot in chat_history:
+        conv.append_message(roles['human'], user)
+        conv.append_message(roles["gpt"], bot)
+    conv.append_message(roles['human'], message)
+    texts = conv.get_prompt()
+    # print(f"get_prompt: \'{texts}\'") # debug
+    return ''.join(texts)
+
+def generate(prompt, max_new_tokens, temperature, top_p, top_k):
+    return llm(prompt,
+            max_tokens=max_new_tokens,
+            stop=["</s>"],
+            temperature=temperature,
+            top_p=top_p,
+            top_k=top_k,
+            stream=False)
+
+
+def get_input_token_length(message: str, chat_history: list[tuple[str, str]], system_prompt: str) -> int:
+    prompt = get_prompt(message, chat_history, system_prompt)
+    input_ids = llm.tokenize(prompt.encode('utf-8'))
+    return len(input_ids)
+
+
+def run(message: str,
+        chat_history: list[tuple[str, str]],
+        system_prompt: str,
+        max_new_tokens: int = 1024,
+        temperature: float = 0.8,
+        top_p: float = 0.95,
+        top_k: int = 50) -> Iterator[str]:
+    prompt = get_prompt(message, chat_history, system_prompt)
+    output = generate(prompt, max_new_tokens, temperature, top_p, top_k)
+    yield output['choices'][0]['text']
+
+    # outputs = []
+    # for resp in streamer:
+    #     outputs.append(resp['choices'][0]['text'])
+    #     yield ''.join(outputs)

requirements.txt

@@ -0,0 +1,9 @@
+accelerate==0.21.0
+bitsandbytes==0.40.2
+gradio==3.37.0
+protobuf==3.20.3
+scipy==1.11.1
+sentencepiece==0.1.99
+torch==2.0.1
+transformers==4.31.0
+llama-cpp-python

style.css

@@ -0,0 +1,16 @@
+h1 {
+  text-align: center;
+}
+
+#duplicate-button {
+  margin: auto;
+  color: white;
+  background: #1565c0;
+  border-radius: 100vh;
+}
+
+#component-0 {
+  max-width: 900px;
+  margin: auto;
+  padding-top: 1.5rem;
+}