Documentation Index
Fetch the complete documentation index at: https://docs.monostate.ai/llms.txt
Use this file to discover all available pages before exploring further.
Autenticación
Configura la autenticación para Hugging Face Hub y W&B.
Token de Hugging Face
Variable de Entorno
export HF_TOKEN="hf_xxxxxxxxxxxxxxxxxxxxx"
En Python
from autotrain.trainers.clm.params import LLMTrainingParams
params = LLMTrainingParams(
model="google/gemma-3-270m",
data_path="./data.jsonl",
project_name="my-model",
token="hf_xxxxxxxxxxxxxxxxxxxxx", # HF token
)
Obtener un Token
- Ve a huggingface.co/settings/tokens
- Haz clic en “New token”
- Selecciona acceso “Write” para push al hub
- Copia el token
Token de W&B
Variable de Entorno
export WANDB_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
En Python
params = LLMTrainingParams(
model="google/gemma-3-270m",
data_path="./data.jsonl",
project_name="my-model",
log="wandb",
wandb_token="xxxxxxxxxxxxxxxxxxxxxxxx",
)
Obtener un Token
- Ve a wandb.ai/authorize
- Copia tu clave de API
Push al Hub
Para enviar modelos al Hugging Face Hub:
params = LLMTrainingParams(
model="google/gemma-3-270m",
data_path="./data.jsonl",
project_name="my-model",
push_to_hub=True,
username="your-hf-username",
token="hf_xxxxxxxxxxxxxxxxxxxxx",
)
Modelos Privados
Accede a modelos privados con tu token:
# Set environment variable
import os
os.environ["HF_TOKEN"] = "hf_xxxxxxxxxxxxxxxxxxxxx"
# Or pass directly
params = LLMTrainingParams(
model="your-org/private-model",
data_path="./data.jsonl",
project_name="my-model",
token="hf_xxxxxxxxxxxxxxxxxxxxx",
)
Datasets Privados
Accede a datasets privados:
params = LLMTrainingParams(
model="google/gemma-3-270m",
data_path="your-org/private-dataset", # HF dataset ID
project_name="my-model",
token="hf_xxxxxxxxxxxxxxxxxxxxx",
)
Manejo Seguro de Tokens
Usando Archivos .env
# .env
HF_TOKEN=hf_xxxxxxxxxxxxxxxxxxxxx
WANDB_API_KEY=xxxxxxxxxxxxxxxxxxxxxxxx
from dotenv import load_dotenv
import os
load_dotenv()
params = LLMTrainingParams(
model="google/gemma-3-270m",
data_path="./data.jsonl",
project_name="my-model",
token=os.getenv("HF_TOKEN"),
)
Nunca Hacer Commit de Tokens
Añade a .gitignore:
Próximos Pasos
Python SDK
Referencia completa de la API
LLM Endpoints
API de entrenamiento LLM
