初始化项目，由ModelHub XC社区提供模型

Model: CreitinGameplays/tesy-0.3
Source: Original Platform

README.md

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+---
+base_model: unsloth/Llama-3.1-8B-Instruct
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- llama
+license: apache-2.0
+language:
+- en
+datasets:
+- CreitinGameplays/mango-v2
+---
+
+# Uploaded finetuned  model
+
+- **Developed by:** CreitinGameplays
+- **License:** apache-2.0
+- **Finetuned from model :** unsloth/Llama-3.1-8B-Instruct
+
+This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+
+Trained using the following parameters:
+```python
+model = FastLanguageModel.get_peft_model(
+    model,
+    r = 16,
+    target_modules = ["q_proj", "k_proj", "v_proj", "o_proj",
+                      "gate_proj", "up_proj", "down_proj",],
+    lora_alpha = 16,
+    lora_dropout = 0,
+    bias = "none",
+    use_gradient_checkpointing = "unsloth",
+    random_state = 3407,
+    use_rslora = False,
+    loftq_config = None,
+)
+
+training_args = TrainingArguments(
+    per_device_train_batch_size = 12,
+    gradient_accumulation_steps = 2,
+    warmup_steps = 100,
+    num_train_epochs = 2,
+    learning_rate = 2e-4,
+    fp16 = not torch.cuda.is_bf16_supported(),
+    bf16 = torch.cuda.is_bf16_supported(),
+    logging_steps = 10,
+    optim = "adamw_8bit",
+    weight_decay = 0.01,
+    lr_scheduler_type = "linear",
+    seed = 3407,
+    output_dir = OUTPUT_DIR,
+    report_to = "none",
+    save_strategy = "steps",
+    save_steps = 50,
+    save_total_limit = 3,
+    load_best_model_at_end = False,
+)
+
+trainer = SFTTrainer(
+    model = model,
+    tokenizer = tokenizer,
+    train_dataset = dataset,
+    dataset_text_field = "text",
+    max_seq_length = max_seq_length,
+    dataset_num_proc = 2,
+    packing = False,
+    args = training_args,
+)
+
+trainer = train_on_responses_only(
+    trainer,
+    instruction_part = "<|start_header_id|>user<|end_header_id|>\n\n", # llama
+    response_part = "<|start_header_id|>assistant<|end_header_id|>\n\n",
+)
+```