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README.md

@@ -1,10 +1,13 @@
 ---
-title: Fastapi T5
-emoji: 🐢
-colorFrom: purple
-colorTo: blue
-sdk: docker
+title: Mistral 7B Instruct GGUF Run On CPU Basic
+emoji: 🔥
+colorFrom: blue
+colorTo: yellow
+sdk: gradio
+sdk_version: 4.3.0
+app_file: app.py
 pinned: false
+license: mit
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+from gpt4all import GPT4All
+from huggingface_hub import hf_hub_download
+
+title = "Apollo-7B-GGUF Run On CPU"
+
+description = """
+🔎 [Apollo-7B](https://huggingface.co/FreedomIntelligence/Apollo-7B) [GGUF format model](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF) , 8-bit quantization balanced quality gguf version, running on CPU. Using [GitHub - llama.cpp](https://github.com/ggerganov/llama.cpp) [GitHub - gpt4all](https://github.com/nomic-ai/gpt4all). 
+
+🔨 Running on CPU-Basic free hardware. Suggest duplicating this space to run without a queue. 
+
+Mistral does not support system prompt symbol (such as ```<<SYS>>```) now, input your system prompt in the first message if you need. Learn more: [Guardrailing Mistral 7B](https://docs.mistral.ai/usage/guardrailing). 
+"""
+
+"""
+[Model From TheBloke/Mistral-7B-Instruct-v0.1-GGUF](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.1-GGUF)
+[Mistral-instruct-v0.1 System prompt](https://docs.mistral.ai/usage/guardrailing)
+"""
+
+model_path = "models"
+model_name = "Apollo-7B-q8_0.gguf"
+hf_hub_download(repo_id="FreedomIntelligence/Apollo-7B-GGUF", filename=model_name, local_dir=model_path, local_dir_use_symlinks=False)
+
+print("Start the model init process")
+model = model = GPT4All(model_name, model_path, allow_download = False, device="cpu")
+print("Finish the model init process")
+
+model.config["promptTemplate"] = "[INST] {0} [/INST]"
+model.config["systemPrompt"] = ""
+model._is_chat_session_activated = False
+
+max_new_tokens = 2048
+
+def generater(message, history, temperature, top_p, top_k):
+    prompt = "<s>"
+    for user_message, assistant_message in history:
+        prompt += model.config["promptTemplate"].format(user_message)
+        prompt += assistant_message + "</s>"
+    prompt += model.config["promptTemplate"].format(message)
+    outputs = []    
+    for token in model.generate(prompt=prompt, temp=temperature, top_k = top_k, top_p = top_p, max_tokens = max_new_tokens, streaming=True):
+        outputs.append(token)
+        yield "".join(outputs)
+
+def vote(data: gr.LikeData):
+    if data.liked:
+        return
+    else:
+        return
+
+chatbot = gr.Chatbot(avatar_images=('resourse/user-icon.png', 'resourse/chatbot-icon.png'),bubble_full_width = False)
+
+additional_inputs=[
+    gr.Slider(
+        label="temperature",
+        value=0.5,
+        minimum=0.0,
+        maximum=2.0,
+        step=0.05,
+        interactive=True,
+        info="Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.",
+    ),
+    gr.Slider(
+        label="top_p",
+        value=1.0,
+        minimum=0.0,
+        maximum=1.0,
+        step=0.01,
+        interactive=True,
+        info="0.1 means only the tokens comprising the top 10% probability mass are considered. Suggest set to 1 and use temperature. 1 means 100% and will disable it",
+    ),
+    gr.Slider(
+        label="top_k",
+        value=40,
+        minimum=0,
+        maximum=1000,
+        step=1,
+        interactive=True,
+        info="limits candidate tokens to a fixed number after sorting by probability. Setting it higher than the vocabulary size deactivates this limit.",
+    )
+]
+
+iface = gr.ChatInterface(
+    fn = generater,
+    title=title,
+    description = description,
+    chatbot=chatbot,
+    additional_inputs=additional_inputs,
+    examples=[
+        ["枸杞有什么疗效"],
+        ["I've taken several courses of antibiotics for recurring infections, and now they seem less effective. Am I developing antibiotic resistance?"],
+    ]
+)
+
+with gr.Blocks(css="resourse/style/custom.css") as demo:
+    chatbot.like(vote, None, None)
+    iface.render()
+
+if __name__ == "__main__":
+    demo.queue(max_size=3).launch()

requirements.txt

@@ -1,7 +1 @@
-fastapi==0.74.*
-requests==2.27.*
-sentencepiece==0.1.*
-torch==1.11.*
-transformers==4.*
-uvicorn[standard]==0.17.*
-gradio
+gpt4all==2.0.2

resourse/style/custom.css

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+h1 {
+  text-align: center;
+}
+
+.contain {
+  max-width: 1000px;
+  margin: auto;
+  padding-top: 1.5rem;
+}