1.
Hello
❱
1.1.
Why Rust
1.2.
Why Wasm
1.3.
Why Solana
2.
Rust
❱
2.1.
R5 - Entry
❱
2.1.1.
Setup
2.1.2.
Enjoy Day 1
2.1.3.
Enjoy Day 2
2.1.4.
Enjoy Day 3
2.1.5.
Enjoy Day 4
2.1.6.
Enjoy Day 5
2.1.7.
Enjoy Day 6
2.1.8.
Enjoy Day 7
2.1.9.
Teardown
2.2.
R4 - Basic
❱
2.2.1.
Parse json with serde
2.2.2.
Fetch json with reqwest
2.2.3.
Fetch multiple with futures
2.2.4.
Fetch multiple with tokio
2.2.5.
Handle multiple result and option
2.2.6.
Fetch and handle with thiserror
2.2.7.
Build a fetch module
2.3.
R3 - Advanced
❱
2.3.1.
Lifetimes
2.3.2.
Create your own lib
2.3.3.
ref
2.3.4.
Deref coercions
2.3.5.
RefCell
2.3.6.
Trait
2.3.7.
Serde
2.3.8.
Enum
2.3.9.
Derive More
2.3.10.
Typed Builder
2.3.11.
Generic Array
2.3.12.
AsRef
2.3.13.
Callback
2.3.14.
Async
2.3.15.
Iterators
2.3.16.
Associated Type Bounds
2.4.
R2 - Expert
❱
2.4.1.
Hello Github Action
2.4.2.
Hello Actix CloudRun
2.4.3.
Hello Diffusers Stable Diffusion
2.5.
R1 - Master
❱
2.5.1.
String
2.5.2.
Marker Types
2.5.3.
Mutex
2.5.4.
Smol
2.5.5.
Signals
3.
Wasm
❱
3.1.
Setup
3.2.
Enjoy
3.3.
Hello Wasm Js
3.4.
React Wasm fetch with reqwest
3.5.
Hello Wasm Sleep and Time
3.6.
Hello Wasm NPM
3.7.
Hello Wasm Firebase
3.8.
Hello Wasm Cloudflare
3.9.
Hello Wasm Fastly
3.10.
Serialize Js data
4.
Solana
❱
4.1.
Hello Solana
4.2.
Fetch balance
4.3.
NFT Memberships
5.
ML
❱
5.1.
Large Language Model
5.2.
Inferences
❱
5.2.1.
ollama
5.2.2.
TabbyML
5.2.3.
WasmEdge
5.2.4.
Hugging Face - Text Generation Inference
5.2.5.
llama.cpp
5.3.
RAG
❱
5.3.1.
Vector Database - Qdrant
5.4.
Embeddings
5.5.
Fine Tuning
5.6.
Frameworks
❱
5.6.1.
Hugging Face - Candle
5.6.2.
Hugging Face - AutoTrain
5.6.3.
Apple - MLX
5.6.4.
PostgresML
5.7.
Stable Diffusion
5.8.
Vision Language Model
5.9.
FLUX.1
5.10.
Voices
❱
5.10.1.
Fish Speech
6.
Bevy
❱
6.1.
Physics with Rapier
7.
BigQuery
❱
7.1.
Inferences
7.2.
Embeddings
7.3.
Search
8.
Bye
Light
Rust
Coal
Navy
Ayu
Gist of Rust
Inferences
candle
// MacOS/Windows/WSL2 // 27GB // 7.71 tokens/sec
llamafile
// MacOS/Windows // 28GB (no gc) // 34.68 tokens/sec
WasmEdge
// MacOS/Windows/WSL2
TabbyML
// MacOS/Windows/WSL2
llama.cpp
// MacOS/Windows // 13GB // 34.01 tokens/sec
ollama
// MacOS/Windows/WSL2