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Dockerfile

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+# Read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
+FROM python:3.9
+
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+
+WORKDIR /app
+
+COPY --chown=user ./requirements.txt requirements.txt
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+
+COPY --chown=user ./TowerInstruct-7B-v0.2.Q8_0.gguf TowerInstruct-7B-v0.2.Q8_0.gguf
+COPY --chown=user ./app.py app.py
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from ctransformers import AutoModelForCausalLM
+from fastapi import FastAPI
+from pydantic import BaseModel
+
+
+llm = AutoModelForCausalLM.from_pretrained("TowerInstruct-7B-v0.2.Q8_0.gguf",
+max_new_tokens = 2084,
+threads = 3,
+)
+
+#Pydantic object
+class validation(BaseModel):
+    prompt: str
+#Fast API
+app = FastAPI()
+
+# <|im_start|>user
+# Translate the following text from Portuguese into English.
+# Portuguese: Um grupo de investigadores lançou um novo modelo para tarefas relacionadas com tradução.
+# English:<|im_end|>
+# <|im_start|>assistant
+
+@app.post("/translate")
+async def stream(item: validation):
+    translation_prompt = 'Below is an instruction that describes a task. Write a response that appropriately completes the request.'
+    S_INST = "<|im_start|>"
+    E_INST = "<|im_end|>"
+    user, assistant = "user", "assistant"
+    prompt = f"{S_INST}{user}\n{translation_prompt}\nChinese:{item.prompt}\nEnglish:{E_INST}\n{S_INST}{assistant}\n"
+    return llm(prompt)

requirements.txt

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+python-multipart
+fastapi
+pydantic
+uvicorn
+requests
+python-dotenv
+ctransformers