>在Databricks上部署DeepSeek R1模型：逐步指南
流行的數據工程平台本指南涵蓋了帳戶設置，使用UI的模型註冊以及通過操場和本地捲曲命令訪問。 Databricks的新手？ Databricks課程簡介提供了Databricks Lakehouse平台及其數據管理功能的全面概述。 要更深入地了解Databricks中的數據管理，請考慮Databricks課程中的數據管理。
註冊DeepSeek R1模型>
%%capture !pip install torch transformers mlflow accelerate torchvision %restart_python
import pandas as pd import mlflow import mlflow.transformers import torch from mlflow.models.signature import infer_signature from transformers import AutoModelForCausalLM, AutoTokenizer, AutoConfig, pipeline model_name = "deepseek-ai/DeepSeek-R1-Distill-Llama-8B" tokenizer = AutoTokenizer.from_pretrained(model_name) config = AutoConfig.from_pretrained(model_name) model = AutoModelForCausalLM.from_pretrained(model_name, config=config, torch_dtype=torch.float16)
text_generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
example_prompt = "How does a computer work?"
example_inputs = pd.DataFrame({"inputs": [example_prompt]})
example_outputs = text_generator(example_prompt, max_length=200)
signature = infer_signature(example_inputs, example_outputs)
print(example_outputs)
<code>[{'generated_text': "How does a computer work? What is the computer? What is the computer used for? What is the computer used for in real life?\n\nI need to answer this question, but I need to do it step by step. I need to start with the very basic level and build up from there. I need to make sure I understand each concept before moving on. I need to use a lot of examples to explain each idea. I need to write my thoughts as if I'm explaining them to someone else, but I need to make sure I understand how to structure the answer properly.\n\nOkay, let's start with the basic level. What is a computer? It's an electronic device, right? And it has a central processing unit (CPU) that does the processing. But I think the central processing unit is more efficient, so maybe it's the CPU. Then, it has memory and storage. I remember that memory is like RAM and storage is like ROM. But wait, I think"}]</code>conda_env = {
"name": "mlflow-env",
"channels": ["defaults", "conda-forge"],
"dependencies": [
"python=3.11",
"pip",
{"pip": ["mlflow", "transformers", "accelerate", "torch", "torchvision"]}
]
}mlflow.transformers.log_model
with mlflow.start_run() as run:
mlflow.transformers.log_model(
transformers_model=text_generator,
artifact_path="deepseek_model",
signature=signature,
input_example=example_inputs,
registered_model_name="deepseek_r1_llama_8b",
conda_env=conda_env
)
在databricks儀表板中，轉到“模型”選項卡。
>
>
$DATABRICKS_TOKEN%%capture !pip install torch transformers mlflow accelerate torchvision %restart_python
>
以上是在Databricks上部署DeepSeek R1：逐步指南的詳細內容。更多資訊請關注PHP中文網其他相關文章！
