if True:
    model.push_to_hub_gguf(
        "my/Repo",
        tokenizer,
        quantization_method = ["q4_k_m", "q8_0", "q5_k_m",],
        token = "hf_myTokenIputHere",
    )

%%capture
import os
if "COLAB_" not in "".join(os.environ.keys()):
    !pip install unsloth
else:
    # Do this only in Colab notebooks! Otherwise use pip install unsloth
    !pip install --no-deps bitsandbytes accelerate xformers==0.0.29.post3 peft trl==0.15.2 triton cut_cross_entropy unsloth_zoo
    !pip install sentencepiece protobuf datasets huggingface_hub hf_transfer
    !pip install --no-deps unsloth

# Load the first dataset and map it to the ShareGPT format
from unsloth.chat_templates import get_chat_template

tokenizer = get_chat_template(
    tokenizer,
    chat_template = "chatml", # Supports zephyr, chatml, mistral, llama, alpaca, vicuna, vicuna_old, unsloth
    mapping = {"role" : "from", "content" : "value", "user" : "human", "assistant" : "gpt"}, # ShareGPT style
    map_eos_token = True, # Maps <|im_end|> to </s> instead
)

def formatting_prompts_func(examples):
    convos = examples["conversations"]
    texts = [tokenizer.apply_chat_template(convo, tokenize = False, add_generation_prompt = False) for convo in convos]
    return { "text" : texts, }
pass

from datasets import load_dataset
dataset = load_dataset("Sweaterdog/Andy-4-FT", split = "train")
dataset = dataset.map(formatting_prompts_func, batched = True,)

from transformers import TrainingArguments
from trl import SFTTrainer
from unsloth import is_bfloat16_supported

trainer = SFTTrainer(
   model=model,
   tokenizer=tokenizer,
   train_dataset=dataset,
   dataset_text_field="text",
   max_seq_length=max_seq_length,
   dataset_num_proc=6,            # Increase CPU processing for faster data loading/preprocessing
   packing=False,
   args=TrainingArguments(
       per_device_train_batch_size=2,
       gradient_accumulation_steps=2,
       warmup_ratio = 0.1,
       num_train_epochs=0.05,
       learning_rate=4e-5,
       fp16= not is_bfloat16_supported(),
       bf16= is_bfloat16_supported(),
       logging_steps= 100,
       optim="adamw_8bit",
       weight_decay=0.01,
       lr_scheduler_type="cosine",
       seed=3407,
       output_dir = "outputs",
       save_steps = 5000,
   ),
)