GITBOOK-129: No subject

Moloejoe · gitbook-bot · commit 7d2ecfbb7bd3 · 2024-03-19T21:23:30.000Z
diff --git a/pgml-cms/docs/resources/benchmarks/ggml-quantized-llm-support-for-huggingface-transformers.md b/pgml-cms/docs/resources/benchmarks/ggml-quantized-llm-support-for-huggingface-transformers.md
@@ -1,3 +1,7 @@
+---
+description: Quantization allows PostgresML to fit larger models in less RAM.
+---
+
 # GGML Quantized LLM support for Huggingface Transformers
 
 Quantization allows PostgresML to fit larger models in less RAM. These algorithms perform inference significantly faster on NVIDIA, Apple and Intel hardware. Half-precision floating point and quantized optimizations are now available for your favorite LLMs downloaded from Huggingface.
diff --git a/pgml-cms/docs/resources/benchmarks/making-postgres-30-percent-faster-in-production.md b/pgml-cms/docs/resources/benchmarks/making-postgres-30-percent-faster-in-production.md
@@ -1,3 +1,9 @@
+---
+description: >-
+  Anyone who runs Postgres at scale knows that performance comes with trade
+  offs.
+---
+
 # Making Postgres 30 Percent Faster in Production
 
 Anyone who runs Postgres at scale knows that performance comes with trade offs. The typical playbook is to place a pooler like PgBouncer in front of your database and turn on transaction mode. This makes multiple clients reuse the same server connection, which allows thousands of clients to connect to your database without causing a fork bomb.
diff --git a/pgml-cms/docs/resources/benchmarks/million-requests-per-second.md b/pgml-cms/docs/resources/benchmarks/million-requests-per-second.md
@@ -1,3 +1,9 @@
+---
+description: >-
+  The question "Does it Scale?" has become somewhat of a meme in software
+  engineering.
+---
+
 # Scaling to 1 Million Requests per Second
 
 The question "Does it Scale?" has become somewhat of a meme in software engineering. There is a good reason for it though, because most businesses plan for success. If your app, online store, or SaaS becomes popular, you want to be sure that the system powering it can serve all your new customers.
diff --git a/pgml-cms/docs/resources/benchmarks/mindsdb-vs-postgresml.md b/pgml-cms/docs/resources/benchmarks/mindsdb-vs-postgresml.md
@@ -1,3 +1,7 @@
+---
+description: "Compare two projects that both aim\Lto provide an SQL interface to ML algorithms and the data they require."
+---
+
 # MindsDB vs PostgresML
 
 ## Introduction
diff --git a/pgml-cms/docs/resources/benchmarks/postgresml-is-8-40x-faster-than-python-http-microservices.md b/pgml-cms/docs/resources/benchmarks/postgresml-is-8-40x-faster-than-python-http-microservices.md
@@ -1,3 +1,7 @@
+---
+description: PostgresML is a simpler alternative to that ever-growing complexity.
+---
+
 # PostgresML is 8-40x faster than Python HTTP microservices
 
 Machine learning architectures can be some of the most complex, expensive and _difficult_ arenas in modern systems. The number of technologies and the amount of required hardware compete for tightening headcount, hosting, and latency budgets. Unfortunately, the trend in the industry is only getting worse along these lines, with increased usage of state-of-the-art architectures that center around data warehouses, microservices and NoSQL databases.
