How can I find the model implementation for a particular model?
- Usually it's avaiable from
transformers/models/xxxx
, e.g., forqwen2_5_vl
#!/bin/bash | |
# === Cache Cleanup Script === | |
# Cleans caches for Homebrew, UV, Hugging Face, and NPM | |
# Usage: bash cleanup.sh [options] | |
# Options: | |
# -a, --all Clean all caches | |
# -b, --brew Clean Homebrew cache | |
# -u, --uv Clean UV cache | |
# -h, --huggingface Clean Hugging Face cache |
How can I find the model implementation for a particular model?
transformers/models/xxxx
, e.g., for qwen2_5_vl
from typing import List, Tuple, Optional, Union, Callable | |
import numpy as np | |
# Define a Tensor type for clarity in this pseudocode | |
Tensor = np.ndarray # In real implementation, this would be a framework-specific tensor type | |
# Qwen2.5-VL Vision Encoder Pseudocode | |
class Qwen25VisionEncoder: | |
def __init__(self, |
Technology | Version | Purpose |
---|---|---|
Next.js | 14.2.0 | React framework with file-based routing, static site generation |
React | 18.2.0 | UI library for component-based development |
TypeScript | 5.3.3 | Static type-checking for JavaScript |
TailwindCSS | 3.4.1 | Utility-first CSS framework |
The walrus operator (:=
) was introduced in Python 3.8 as part of PEP 572. It's officially called the "assignment expression" operator, but it earned its nickname because :=
resembles a walrus with tusks when viewed sideways. This operator allows you to assign values to variables as part of an expression, rather than as a separate statement.
The syntax is:
variable := expression
Term | Description |
---|---|
SM (Streaming Multiprocessor) | Computational unit in NVIDIA GPUs; Hopper has up to 132 SMs |
Warp | Group of 32 threads that execute in lockstep |
Thread Block | Group of threads that execute on the same SM and can synchronize |
Grid | Collection of thread blocks that execute the same kernel |
FROM codercom/code-server:latest
USER root
# Install system dependencies
RUN apt-get update && apt-get install -y \
python3-pip \
python3-venv \
This is an excellent LangGraph cheat sheet! It provides a comprehensive and practical overview of LangGraph's key features and usage. Here's a slightly refined version with added clarity and formatting for better readability:
from typing import TypedDict, Dict, Any, Callable
from langchain_core.runnables import Runnable
TS (TypeScript) is a strongly-typed superset of JavaScript developed by Microsoft. It adds optional static typing, modern JavaScript features, and tooling to enhance code quality and maintainability. TypeScript compiles to plain JavaScript and is widely used for large-scale applications.
let name: string = "John";
let age: number = 30;