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Update examples titles for SEO #996

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2 changes: 1 addition & 1 deletion 05_scheduling/hackernews_alerts.py
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# lambda-test: false
# tags: ["featured"]
# ---
# # Hacker News Slackbot
# # Run cron jobs in the cloud to search Hacker News

# In this example, we use Modal to deploy a cron job that periodically queries Hacker News for
# new posts matching a given search term, and posts the results to Slack.
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2 changes: 1 addition & 1 deletion 06_gpu_and_ml/llm-serving/vllm_inference.py
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# tags: ["use-case-lm-inference", "featured"]
# ---

# # Run an OpenAI-Compatible vLLM Server
# # Run OpenAI-compatible LLM inference with LLaMA 3.1-8B and vLLM

# LLMs do more than just model language: they chat, they produce JSON and XML, they run code, and more.
# This has complicated their interface far beyond "text-in, text-out".
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2 changes: 1 addition & 1 deletion 06_gpu_and_ml/llm-structured/jsonformer_generate.py
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@@ -1,7 +1,7 @@
# ---
# lambda-test: false
# ---
# # Generate synthetic data with Jsonformer
# # Structured output generation with Jsonformer
#
# [Jsonformer](https://github.com/1rgs/jsonformer) is a tool that generates structured synthetic data using LLMs.
# You provide a JSON spec and it generates a JSON object following the spec. It's a
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2 changes: 1 addition & 1 deletion 06_gpu_and_ml/obj_detection_webcam/webcam.py
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# deploy: true
# tags: ["use-case-image-video-3d", "featured"]
# ---
# # Machine learning model inference endpoint that uses the webcam
# # Real-time object detection via webcam
#
# This example creates a web endpoint that uses a Huggingface model for object detection.
#
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2 changes: 1 addition & 1 deletion 06_gpu_and_ml/stable_diffusion/flux.py
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# tags: ["use-case-image-video-3d", "featured"]
# ---

# # Run Flux fast with `torch.compile` on Hopper GPUs
# # Run Flux fast on H100s with `torch.compile`

# In this guide, we'll run Flux as fast as possible on Modal using open source tools.
# We'll use `torch.compile` and NVIDIA H100 GPUs.
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2 changes: 1 addition & 1 deletion 06_gpu_and_ml/text-to-video/mochi.py
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# cmd: ["modal", "run", "--detach", "06_gpu_and_ml/text-to-video/mochi.py", "--num-inference-steps", "64"]
# ---

# # Generate videos from text prompts with Mochi
# # Text-to-video generation with Mochi

# This example demonstrates how to run the [Mochi 1](https://github.com/genmoai/models)
# video generation model by [Genmo](https://www.genmo.ai/) on Modal.
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2 changes: 1 addition & 1 deletion 06_gpu_and_ml/yolo/finetune_yolo.py
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# args: ["--no-quick-check"]
# tags: ["use-case-image-video-3d", "use-case-finetuning"]
# ---
# # Fine-Tuning and Inference for Computer Vision with YOLO
# # Fine-tune open source YOLO models for object detection
#
# Example by [@Erik-Dunteman](https://github.com/erik-dunteman) and [@AnirudhRahul](https://github.com/AnirudhRahul/).

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