Using Falcon 7B on GCP Vertex AI
Implementation guide · Falcon · Technology Innovation Institute (TII)
Quick Start
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Code Examples
pip install google-cloud-aiplatformGOOGLE_CLOUD_PROJECTfalcon-7bFor Google-published models use the model name directly, e.g. "gemini-2.0-flash-001". For third-party publishers (Anthropic, Meta, etc.) use the full publisher path, e.g. "publishers/anthropic/models/claude-3-5-sonnet-v2@20241022".
import os
import vertexai
from vertexai.generative_models import GenerativeModel
# Reads GOOGLE_CLOUD_PROJECT from env; authenticates via Application Default Credentials
vertexai.init(project=os.environ["GOOGLE_CLOUD_PROJECT"], location="us-central1")
model = GenerativeModel("falcon-7b")
response = model.generate_content("Hello")
print(response.text)About GCP Vertex AI
Google Cloud Vertex AI is a comprehensive machine learning platform that provides end-to-end solutions for developing, deploying, and managing AI models. The platform offers a unified interface that integrates various tools and services, enabling users to efficiently handle the entire machine learning lifecycle. Key features include AutoML capabilities for building custom models with minimal coding, a managed notebook environment for prototyping, and robust MLOps tools for model monitoring and versioning. Vertex AI supports both pre-trained models and custom training, making it versatile for a wide range of applications such as natural language processing, image recognition, and predictive analytics. The platform's design focuses on increasing productivity and accelerating time-to-market for AI solutions. By consolidating multiple AI tools into a single ecosystem, Vertex AI reduces manual effort and enhances collaboration among data scientists and engineers. Its scalable architecture allows organizations to efficiently manage large datasets and complex models, while the pay-as-you-go pricing model makes it accessible for businesses of all sizes. Additionally, Vertex AI's integration with popular open-source frameworks like TensorFlow and PyTorch enables users to leverage existing models and tools, fostering innovation and facilitating the development of customized AI applications tailored to specific business needs.
Vertex AI is Google Cloud's managed AI platform, offering access to Gemini models and hundreds of partner models alongside tools for fine-tuning, grounding, vector search, and end-to-end MLOps pipelines.
Pricing on GCP Vertex AI
Capabilities
About Falcon 7B
Falcon-7B, developed by the Technology Innovation Institute, is a cutting-edge large language model boasting a decoder-only architecture with 7 billion parameters. It's trained on 1,500 billion tokens from the curated web dataset, RefinedWeb, enhancing its performance in language tasks. The model is equipped with advanced features like FlashAttention and multiquery attention, optimizing speed and memory usage. With 32 layers and rotary positional embeddings, it manages a sequence length of up to 2048 tokens efficiently. Renowned for tasks such as text generation, summarization, translation, and conversational AI, Falcon-7B is open-source under Apache 2.0, suitable even for consumer hardware, needing at least 16GB of memory for inference 236.