Weights & Biases vs Hugging Face

import wandb

# Initialize a run
wandb.init(project="my-project", config={
    "learning_rate": 0.001,
    "epochs": 10,
    "batch_size": 32,
})

for epoch in range(wandb.config.epochs):
    train_loss, val_loss, accuracy = train_one_epoch(model, epoch)

    # Log metrics
    wandb.log({
        "epoch": epoch,
        "train/loss": train_loss,
        "val/loss": val_loss,
        "val/accuracy": accuracy,
    })

wandb.finish()

import { HfInference } from '@huggingface/inference';

const hf = new HfInference(process.env.HUGGINGFACE_API_KEY);

// Text generation
const result = await hf.textGeneration({
  model: 'mistralai/Mistral-7B-Instruct-v0.3',
  inputs: 'Explain quantum computing in one sentence:',
  parameters: { max_new_tokens: 100, temperature: 0.7 },
});

console.log(result.generated_text);