Duplicate from PY007/SLM-Chatbox-Preview

Co-authored-by: Zhang Peiyuan <[email protected]>

.gitattributes

@@ -0,0 +1,35 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,13 @@
+---
+title: SLM Chatbox Preview
+emoji: 💻
+colorFrom: indigo
+colorTo: yellow
+sdk: gradio
+sdk_version: 3.39.0
+app_file: app.py
+pinned: false
+duplicated_from: PY007/SLM-Chatbox-Preview
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,139 @@
+import os
+import gc
+from string import Template
+from threading import Thread
+
+import torch
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM, BatchEncoding, TextIteratorStreamer
+
+
+tokenizer = AutoTokenizer.from_pretrained(
+    "PY007/LiteChat-Preview",
+)
+model = AutoModelForCausalLM.from_pretrained(
+    "PY007/LiteChat-Preview",
+    trust_remote_code=True,
+    device_map="auto",
+    torch_dtype=torch.float16
+)
+model.eval()
+
+
+max_context_length = model.config.max_position_embeddings
+max_new_tokens = 1024
+
+
+prompt_template = Template("""\
+### Instruction: $human
+### Response: $bot\
+""")
+
+
+system_prompt = "Below is an instruction that describes a task. Write a response that appropriately completes the request."
+system_prompt_tokens = tokenizer([f"{system_prompt}\n\n"], return_tensors="pt")
+max_sys_tokens = system_prompt_tokens['input_ids'].size(-1)
+
+
+def bot(history):
+    history = history or []
+
+    # Inject prompt formatting into the history
+    prompt_history = []
+    for human, bot in history:
+        if bot is not None:
+            bot = bot.replace("<br>", "\n")
+            bot = bot.rstrip()
+        prompt_history.append(
+            prompt_template.substitute(
+                human=human, bot=bot if bot is not None else "")
+        )
+
+    msg_tokens = tokenizer(
+        "\n\n".join(prompt_history).strip(),
+        return_tensors="pt",
+        add_special_tokens=False  # Use <BOS> from the system prompt
+    )
+
+    # Take only the most recent context up to the max context length and prepend the
+    # system prompt with the messages
+    max_tokens = -max_context_length + max_new_tokens + max_sys_tokens
+    inputs = BatchEncoding({
+        k: torch.concat([system_prompt_tokens[k], msg_tokens[k][:, max_tokens:]], dim=-1)
+        for k in msg_tokens
+    }).to('cuda')
+    # inputs = BatchEncoding({
+    #     k: torch.concat([system_prompt_tokens[k], msg_tokens[k][:, max_tokens:]], dim=-1)
+    #     for k in msg_tokens
+    # })
+    # Remove `token_type_ids` b/c it's not yet supported for LLaMA `transformers` models
+    if inputs.get("token_type_ids", None) is not None:
+        inputs.pop("token_type_ids")
+
+    streamer = TextIteratorStreamer(
+        tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True
+    )
+    generate_kwargs = dict(
+        inputs,
+        streamer=streamer,
+        max_new_tokens=max_new_tokens,
+        do_sample=True,
+        top_p=0.95,
+        top_k=50,
+        temperature=0.7,
+    )
+    thread = Thread(target=model.generate, kwargs=generate_kwargs)
+    thread.start()
+
+    partial_text = ""
+    for new_text in streamer:
+        # Process out the prompt separator
+        new_text = new_text.replace("<br>", "\n")
+        if "###" in new_text:
+            new_text = new_text.split("###")[0]
+            partial_text += new_text.strip()
+            history[-1][1] = partial_text
+            break
+        else:
+            # Filter empty trailing new lines
+            if new_text == "\n":
+                new_text = new_text.strip()
+            partial_text += new_text
+            history[-1][1] = partial_text
+        yield history
+    return partial_text
+
+
+def user(user_message, history):
+    return "", history + [[user_message, None]]
+
+
+with gr.Blocks() as demo:
+    gr.Markdown("# SLM-Chat by Zhang Peiyuan, StatNLP")
+    gr.HTML("<a href='https://huggingface.co/PY007/SLM-Alpaca-Finetuned-Preview'><code>PY007/SLM-Alpaca-Finetuned-Preview</a>")
+
+    chatbot = gr.Chatbot([], elem_id="chatbot").style(height=500)
+    state = gr.State([])
+    with gr.Row():
+        with gr.Column():
+            msg = gr.Textbox(
+                label="Send a message",
+                placeholder="Send a message",
+                show_label=False
+            ).style(container=False)
+        with gr.Column():
+            with gr.Row():
+                submit = gr.Button("Send")
+                stop = gr.Button("Stop")
+                clear = gr.Button("Clear History")
+
+    submit_event = msg.submit(user, inputs=[msg, chatbot], outputs=[msg, chatbot], queue=False).then(
+        fn=bot, inputs=[chatbot], outputs=[chatbot], queue=True)
+    submit_click_event = submit.click(user, inputs=[msg, chatbot], outputs=[msg, chatbot], queue=False).then(
+        fn=bot, inputs=[chatbot], outputs=[chatbot], queue=True)
+
+    stop.click(fn=None, inputs=None, outputs=None, cancels=[submit_event, submit_click_event], queue=False)
+    clear.click(lambda: None, None, [chatbot], queue=True)
+
+demo.queue(max_size=32)
+demo.launch()

requirements.txt

@@ -0,0 +1,5 @@
+accelerate
+torch
+bitsandbytes
+transformers>=4.28.0,<4.29.0
+scipy