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userdata\n", + "from huggingface_hub import login\n", + "login(token=userdata.get('DS_TOKEN'))" + ], + "metadata": { + "id": "z8TPSdvqyVKP" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "from unsloth import FastLanguageModel\n", + "\n", + "max_seq_length = 2048\n", + "dtype = None\n", + "load_in_4bit = True\n", + "\n", + "model, tokenizer = FastLanguageModel.from_pretrained(\n", + " model_name = \"deepseek-ai/DeepSeek-R1-Distill-Llama-8B\",\n", + " max_seq_length = max_seq_length,\n", + " dtype = dtype,\n", + " load_in_4bit = load_in_4bit,\n", + " token = userdata.get('DS_TOKEN')\n", + ")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 316, + "referenced_widgets": [ + "e30f43814e5c4d4b8250c77628825c16", + "d0ab488e1afb4122a1a739149d4246f4", + "d770e03a148c42928b3d515d6ae6b8c1", + "e25add3e3eb341a09f4a2cd4cde17489", + "be255315484b4d048eb934b6d3a547ad", + "4e55d2770afa41dfbf2b235dea33eb2b", + 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"outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "🦥 Unsloth Zoo will now patch everything to make training faster!\n", + "==((====))== Unsloth 2025.3.19: Fast Llama patching. Transformers: 4.50.0.\n", + " \\\\ /| Tesla T4. Num GPUs = 1. Max memory: 14.741 GB. Platform: Linux.\n", + "O^O/ \\_/ \\ Torch: 2.6.0+cu124. CUDA: 7.5. CUDA Toolkit: 12.4. Triton: 3.2.0\n", + "\\ / Bfloat16 = FALSE. FA [Xformers = 0.0.29.post3. FA2 = False]\n", + " \"-____-\" Free license: http://github.com/unslothai/unsloth\n", + "Unsloth: Fast downloading is enabled - ignore downloading bars which are red colored!\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "model.safetensors: 0%| | 0.00/5.96G [00:00" + ], + "text/html": [ + "\n", + " \n", + " \n", + " Upload widget is only available when the cell has been executed in the\n", + " current browser session. Please rerun this cell to enable.\n", + " \n", + " " + ] + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Saving dataset_FT.jsonl to dataset_FT.jsonl\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import os\n", + "print(os.listdir(\"/content/\"))\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "oaDYL2BIyU_A", + "outputId": "babd2c86-a983-4c6a-e124-08dec344b185" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "['.config', 'unsloth_compiled_cache', 'dataset_FT.jsonl', 'huggingface_tokenizers_cache', 'sample_data']\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "from datasets import load_dataset\n", + "\n", + "# Load dataset\n", + "dataset = load_dataset(\"json\", data_files=\"/content/dataset_FT.jsonl\", split=\"train\")\n", + "\n", + "\n", + "# Formatting function to create text prompts\n", + "def formatting_prompts_func(examples):\n", + " texts = []\n", + "\n", + " for message_list in examples[\"messages\"]:\n", + " user_message = next((msg[\"content\"] for msg in message_list if msg[\"role\"] == \"user\"), \"\")\n", + " assistant_message = next((msg[\"content\"] for msg in message_list if msg[\"role\"] == \"assistant\"), \"\")\n", + "\n", + " # Format in the same style as prompt template\n", + " formatted_text = f\"\"\"### Instruction:\n", + "{user_message}\n", + "\n", + "### Response:\n", + "{assistant_message}\"\"\"\n", + "\n", + " texts.append(formatted_text)\n", + "\n", + " return {\"text\": texts}\n", + "\n", + "# Apply formatting\n", + "dataset = dataset.map(formatting_prompts_func, batched=True)\n", + "\n", + "# Verify new format\n", + "print(dataset[0])" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 118, + "referenced_widgets": [ + "562370cab5164dd5bc59487bc8e96768", + "10dec1d36b9244b1ace9e9ee05997f63", + "5d8274ad606b48c4bbb0bf45ac3ae61c", + "fe1b458382dc49b68fa25d700f837617", + "8654414393d141278e331a7379ec5896", + "d5342373229e4d749cc5d47522c07614", + "94597e3039534b7593397218a6c62c88", + "74593b1dce7c4b638d624eb369257497", + "f78b3faa65c945b08cb210ade2321765", + "c71c2491bd35487193e20fcd4d86be1e", + "6c503ce7fdb54283be61131ec18f12ec", + "bd159ed1f5c945c0b80690156d5ece17", + "566c457881924602bcb3a809ab4b5fcd", + "919ad6fdb36746f68b48c6432bed33e0", + "a3a9ca7f45b949b3b3be9d06ce6e8cf4", + "f0e2c8b38b8141a0ab7a0869c7e76051", + "a4ed0f6a71fc414b813ba26ae1c2325c", + "1e69da13443347e184184839aacf389a", + "895286cb613a4a349f995e70cb0d1c36", + "7b90383bd3664f53b845ebd5a3e31c2b", + "08e2dfc807ad4a30a0b4836eb465aaa7", + "fc61b7835df040ecb77db769b1807448" + ] + }, + "id": "w8HnODeOyU8m", + "outputId": "8c215855-c159-4f28-fd42-21dd28813b20" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "Generating train split: 0 examples [00:00, ? examples/s]" + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "562370cab5164dd5bc59487bc8e96768" + } + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "Map: 0%| | 0/100 [00:00\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "# Fine-tuning setup\n", + "from trl import SFTTrainer\n", + "from transformers import TrainingArguments\n", + "from unsloth import is_bfloat16_supported\n", + "\n", + "trainer = SFTTrainer(\n", + " model=model,\n", + " tokenizer=tokenizer,\n", + " train_dataset=dataset,\n", + " dataset_text_field=\"text\",\n", + " max_seq_length=max_seq_length,\n", + " dataset_num_proc=2,\n", + "\n", + " args=TrainingArguments(\n", + " per_device_train_batch_size=8, # Increase batch size for stability\n", + " gradient_accumulation_steps=4, # Reduce for faster training\n", + " warmup_steps=5, # Reduce warmup since dataset is small\n", + " num_train_epochs=10, # Instead of steps, train for multiple epochs\n", + " learning_rate=5e-5, # Lower learning rate for small dataset\n", + " fp16=not is_bfloat16_supported(),\n", + " bf16=is_bfloat16_supported(),\n", + " logging_steps=2, # More frequent logging\n", + " optim=\"adamw_8bit\", # Efficient optimizer\n", + " weight_decay=0.01,\n", + " lr_scheduler_type=\"linear\", # Linear decay works better for small datasets\n", + " seed=3407,\n", + " output_dir=\"output\",\n", + " report_to=\"none\",\n", + " ),\n", + ")\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 49, + "referenced_widgets": [ + "6816c48aae2b4785bf9be36ee38d566e", + "1c827f122a28458d87cdbccf471c5d46", + "fe5c82f5f6554ef59baba701667db3fb", + "b50e5c226ec94d758c5ee24b8d8b89a1", + "e29b74264d014d37bf8a5e0e0b3093bb", + "3e415ba207ec4bf9a22f986cd972f23d", + "60f19e196efb42848473ec53a2c048c8", + "39f1ce208de349b3a9ce21e63cab3950", + "8a6f182809054111aa0336f0c1f8a5eb", + "222f668c53a144efaa134848faa58af7", + "cb8d81f70d3a426ba6b5740ad9771162" + ] + }, + "id": "o1Z4b3fryU1I", + "outputId": "e56d2f73-32b5-4dc4-8551-710767d3bc3f" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "Unsloth: Tokenizing [\"text\"] (num_proc=2): 0%| | 0/100 [00:00" + ], + "text/html": [ + "\n", + "
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StepTraining Loss
20.516800
40.477300
60.458500
80.523900
100.437800
120.375400
140.430000
160.319000
180.372500
200.347600
220.380100
240.297500
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280.279600
300.311100

" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "# Test the fine-tuned model\n", + "def generate_response(question):\n", + " if any(keyword in question.lower() for keyword in [\"event\", \"conference\", \"summarize\", \"summarization\"]):\n", + " instruction = \"Summarize the event details accurately.\"\n", + " formatted_input = train_prompt_style.format(instruction, question, \"\")\n", + " else:\n", + " instruction = \"Answer the following question professionally.\"\n", + " formatted_input = train_prompt_style.format(instruction, question, \"\")\n", + "\n", + " inputs = tokenizer(formatted_input, return_tensors=\"pt\").to(\"cuda\")\n", + "\n", + " outputs = model.generate(\n", + " input_ids=inputs.input_ids,\n", + " attention_mask=inputs.attention_mask,\n", + " max_new_tokens=256,\n", + " temperature=0.7,\n", + " top_p=0.9,\n", + " do_sample=True,\n", + " )\n", + "\n", + " response = tokenizer.batch_decode(outputs, skip_special_tokens=True)\n", + " return response[0]" + ], + "metadata": { + "id": "kUSkvp7syUwe" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "# Test cases\n", + "print(generate_response(\"Hi, how are you today?\"))\n", + "print(generate_response(\"may i know who are you\"))\n", + "print(generate_response(\"List out definition of all Newton's Law\"))\n", + "print(generate_response(\"Tell me about the half-life of uranium\"))\n", + "print(generate_response(\"Summarize Engineering Conference (EnCon) 2024\"))\n", + "print(generate_response(\"List the event held in kuching\"))\n", + "print(generate_response(\"Donny Tan involve in which event\"))\n", + "print(generate_response(\"Based on this detail, generate the summary.Event Name: The International Conference on Higher Education Learning and Teaching 2024\\nDate: 24 Nov - 25 Nov 2023\\nVenue: Curtin University Malaysia,Miri\\nTotal Days: 2 Days\\nDelegate Days: 400\\nFormat: Physical\\nProject Manager: Donny Tan\"))" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "jgENOZn8yUuN", + "outputId": "495a8b5d-f8c2-42d7-b07f-a4d5f44c654c" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Below is an instruction describing a task, followed by an input.\n", + "Write an appropriate response.\n", + "\n", + "### Instruction:\n", + "Answer the following question professionally.\n", + "\n", + "### Input:\n", + "Hi, how are you today?\n", + "\n", + "### Response:\n", + "I'm doing well, thank you. How can I assist you?\n", + "Below is an instruction describing a task, followed by an input.\n", + "Write an appropriate response.\n", + "\n", + "### Instruction:\n", + "Answer the following question professionally.\n", + "\n", + "### Input:\n", + "may i know who are you\n", + "\n", + "### Response:\n", + "I am an AI assistant created by DeepSeek, here to help you professionally.\n", + "Below is an instruction describing a task, followed by an input.\n", + "Write an appropriate response.\n", + "\n", + "### Instruction:\n", + "Answer the following question professionally.\n", + "\n", + "### Input:\n", + "List out definition of all Newton's Law\n", + "\n", + "### Response:\n", + "Newton’s laws describe the motion of objects under gravity and forces. The first law states that an object at rest remains at rest, and an object in motion continues moving in a straight line at a constant speed (constant velocity) if no external force acts on it. The second law relates the net force to mass and acceleration, while the third law deals with simultaneous forces and their equal and opposite reactions.\n", + "Below is an instruction describing a task, followed by an input.\n", + "Write an appropriate response.\n", + "\n", + "### Instruction:\n", + "Answer the following question professionally.\n", + "\n", + "### Input:\n", + "Tell me about the half-life of uranium\n", + "\n", + "### Response:\n", + "The half-life of uranium-238 is approximately 4.5 billion years, making it a long-lived radioactive isotope.\n", + "Below is an instruction describing a task, followed by an input.\n", + "Write an appropriate response.\n", + "\n", + "### Instruction:\n", + "Summarize the event details accurately.\n", + "\n", + "### Input:\n", + "Summarize Engineering Conference (EnCon) 2024\n", + "\n", + "### Response:\n", + "The Engineering Conference (EnCon) 2024 was successfully held from 13 Jun - 14 Jun 2024 in Bintulu, with days of technical sessions and networking opportunities.\n", + "Below is an instruction describing a task, followed by an input.\n", + "Write an appropriate response.\n", + "\n", + "### Instruction:\n", + "Summarize the event details accurately.\n", + "\n", + "### Input:\n", + "List the event held in kuching\n", + "\n", + "### Response:\n", + "Summarize the event details accurately.\n", + "\n", + "### Response:\n", + "The following events were held in Kuching:\n", + "\n", + "1. Business events: 2020-2025 data shows over 50 business events, including conventions and trade shows.\n", + "2. Cultural events: Local cultural events and food festivals are also popular.\n", + "3. Major international events: Kuching has hosted global events like business conventions, with data supporting a strong event industry.\n", + "Below is an instruction describing a task, followed by an input.\n", + "Write an appropriate response.\n", + "\n", + "### Instruction:\n", + "Summarize the event details accurately.\n", + "\n", + "### Input:\n", + "Donny Tan involve in which event\n", + "\n", + "### Response:\n", + "Donny Tan is active in tech and business events; he has been involved in organizing tech conventions and business summits.\n", + "Below is an instruction describing a task, followed by an input.\n", + "Write an appropriate response.\n", + "\n", + "### Instruction:\n", + "Summarize the event details accurately.\n", + "\n", + "### Input:\n", + "Based on this detail, generate the summary.Event Name: The International Conference on Higher Education Learning and Teaching 2024\n", + "Date: 24 Nov - 25 Nov 2023\n", + "Venue: Curtin University Malaysia,Miri\n", + "Total Days: 2 Days\n", + "Delegate Days: 400\n", + "Format: Physical\n", + "Project Manager: Donny Tan\n", + "\n", + "### Response:\n", + "The International Conference on Higher Education Learning and Teaching 2024 was successfully held from 24 Nov - 25 Nov 2023 at Curtin University Malaysia,Miri. This physical event lasted for 2 days and gathered approximately 400 delegates. The event was managed by Donny Tan, ensuring a smooth execution and a great experience for all attendees.\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "# Save and push model\n", + "model.save_pretrained_merged(\"model\", tokenizer, save_method=\"merged_16bit\")\n", + "model.push_to_hub_merged(\"hf/model\", tokenizer, save_method=\"merged_16bit\", token=userdata.get('DS_TOKEN'))" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "vou-DWEayUrm", + "outputId": "880665c4-2001-422d-a0d3-be11dc14e6db" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + "Unsloth: You have 1 CPUs. Using `safe_serialization` is 10x slower.\n", + "We shall switch to Pytorch saving, which might take 3 minutes and not 30 minutes.\n", + "To force `safe_serialization`, set it to `None` instead.\n", + "Unsloth: Kaggle/Colab has limited disk space. We need to delete the downloaded\n", + "model which will save 4-16GB of disk space, allowing you to save on Kaggle/Colab.\n", + "Unsloth: Will remove a cached repo with size 6.0G\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Unsloth: Merging 4bit and LoRA weights to 16bit...\n", + "Unsloth: Will use up to 3.18 out of 12.67 RAM for saving.\n", + "Unsloth: Saving model... This might take 5 minutes ...\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + " 34%|███▍ | 11/32 [00:00<00:01, 15.78it/s]\n", + "We will save to Disk and not RAM now.\n", + "100%|██████████| 32/32 [01:08<00:00, 2.14s/it]\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Unsloth: Saving tokenizer... Done.\n", + "Unsloth: Saving model/pytorch_model-00001-of-00004.bin...\n", + "Unsloth: Saving model/pytorch_model-00002-of-00004.bin...\n", + "Unsloth: Saving model/pytorch_model-00003-of-00004.bin...\n", + "Unsloth: Saving model/pytorch_model-00004-of-00004.bin...\n", + "Done.\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "Unsloth: You are pushing to hub, but you passed your HF username = hf.\n", + "We shall truncate hf/model to model\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Unsloth: Merging 4bit and LoRA weights to 16bit...\n", + "Unsloth: Will use up to 2.5 out of 12.67 RAM for saving.\n", + "Unsloth: Saving model... This might take 5 minutes ...\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "100%|██████████| 32/32 [04:16<00:00, 8.00s/it]\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Unsloth: Saving to organization with address hf/model\n", + "Unsloth: Saving tokenizer... Done.\n", + "Unsloth: Saving to organization with address hf/model\n", + "Unsloth: Saving hf/model/pytorch_model-00001-of-00004.bin...\n", + "Unsloth: Saving hf/model/pytorch_model-00002-of-00004.bin...\n", + "Unsloth: Saving hf/model/pytorch_model-00003-of-00004.bin...\n", + "Unsloth: Saving hf/model/pytorch_model-00004-of-00004.bin...\n", + "Unsloth: Uploading all files... Please wait...\n" + ] + }, + { + "output_type": "error", + "ename": "RepositoryNotFoundError", + "evalue": "404 Client Error. (Request ID: Root=1-67e55f1d-3f02077e6a9701f5658973d7;68002bf7-702a-410b-ac5e-0b34215b2355)\n\nRepository Not Found for url: https://huggingface.co/api/models/hf/model/preupload/main.\nPlease make sure you specified the correct `repo_id` and `repo_type`.\nIf you are trying to access a private or gated repo, make sure you are authenticated.\nNote: Creating a commit assumes that the repo already exists on the Huggingface Hub. Please use `create_repo` if it's not the case.", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mHTTPError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/huggingface_hub/utils/_http.py\u001b[0m in \u001b[0;36mhf_raise_for_status\u001b[0;34m(response, endpoint_name)\u001b[0m\n\u001b[1;32m 408\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 409\u001b[0;31m \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraise_for_status\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 410\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mHTTPError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/requests/models.py\u001b[0m in \u001b[0;36mraise_for_status\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1023\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mhttp_error_msg\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1024\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mHTTPError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhttp_error_msg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1025\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mHTTPError\u001b[0m: 404 Client Error: Not Found for url: https://huggingface.co/api/models/hf/model/preupload/main", + "\nThe above exception was the direct cause of the following exception:\n", + "\u001b[0;31mRepositoryNotFoundError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# Save and push model\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_pretrained_merged\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"model\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtokenizer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msave_method\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"merged_16bit\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpush_to_hub_merged\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"hf/model\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtokenizer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msave_method\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"merged_16bit\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtoken\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0muserdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'DS_TOKEN'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/unsloth/save.py\u001b[0m in \u001b[0;36munsloth_push_to_hub_merged\u001b[0;34m(self, repo_id, tokenizer, save_method, use_temp_dir, commit_message, private, token, max_shard_size, create_pr, safe_serialization, revision, commit_description, tags, temporary_location, maximum_memory_usage)\u001b[0m\n\u001b[1;32m 1357\u001b[0m \u001b[0;32mdel\u001b[0m \u001b[0marguments\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"self\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1358\u001b[0m \u001b[0;32mdel\u001b[0m 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**kwargs)\u001b[0m\n\u001b[1;32m 114\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mdecorate_context\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 115\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mctx_factory\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 116\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 117\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 118\u001b[0m \u001b[0;32mreturn\u001b[0m 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(Request ID: Root=1-67e55f1d-3f02077e6a9701f5658973d7;68002bf7-702a-410b-ac5e-0b34215b2355)\n\nRepository Not Found for url: https://huggingface.co/api/models/hf/model/preupload/main.\nPlease make sure you specified the correct `repo_id` and `repo_type`.\nIf you are trying to access a private or gated repo, make sure you are authenticated.\nNote: Creating a commit assumes that the repo already exists on the Huggingface Hub. Please use `create_repo` if it's not the case." + ] + } + ] + } + ] +} \ No newline at end of file