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# requires-python = ">=3.10"
# dependencies = [
# "trl>=0.12.0",
# "peft>=0.7.0",
# "transformers>=4.36.0",
# "accelerate>=0.24.0",
# "trackio",
# "datasets",
# ]
# ///
import os
import huggingface_hub
import trackio
from datasets import load_dataset
from peft import LoraConfig
from trl import SFTTrainer, SFTConfig
# Explicit login with token from secrets
token = os.environ.get("HF_TOKEN")
if token:
huggingface_hub.login(token=token)
print("Logged in to HF Hub")
else:
print("WARNING: No HF_TOKEN found!")
print("Loading dataset...")
dataset = load_dataset("erik1988/way2agi-memory-agent-sft", data_files="memory-agent-sft-v3-merged.jsonl", split="train")
print(f"Dataset loaded: {len(dataset)} examples")
dataset_split = dataset.train_test_split(test_size=0.1, seed=42)
train_dataset = dataset_split["train"]
eval_dataset = dataset_split["test"]
print(f"Train: {len(train_dataset)}, Eval: {len(eval_dataset)}")
peft_config = LoraConfig(
r=32,
lora_alpha=64,
lora_dropout=0.05,
bias="none",
task_type="CAUSAL_LM",
target_modules=["q_proj", "k_proj", "v_proj", "o_proj", "gate_proj", "up_proj", "down_proj"],
)
config = SFTConfig(
output_dir="elias-memory-agent-v1",
push_to_hub=True,
hub_model_id="erik1988/elias-memory-agent-v1",
hub_strategy="every_save",
hub_token=token,
max_length=None,
num_train_epochs=5,
per_device_train_batch_size=2,
gradient_accumulation_steps=4,
learning_rate=2e-4,
logging_steps=5,
save_strategy="steps",
save_steps=50,
save_total_limit=3,
eval_strategy="steps",
eval_steps=50,
warmup_ratio=0.1,
lr_scheduler_type="cosine",
gradient_checkpointing=True,
report_to="trackio",
project="way2agi-memory-agent",
run_name="memory-agent-sft-v3-qwen1.5b",
)
print("Initializing trainer...")
trainer = SFTTrainer(
model="Qwen/Qwen2.5-1.5B-Instruct",
train_dataset=train_dataset,
eval_dataset=eval_dataset,
args=config,
peft_config=peft_config,
)
print("Starting training...")
trainer.train()
print("Pushing to Hub...")
trainer.push_to_hub()
trackio.finish()
print("Done! Model at: https://huggingface.co/erik1988/elias-memory-agent-v1")
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