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Model: StudentLLM/Alpagasus-2-13b-QLoRA-merged
Source: Original Platform

.gitattributes

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README.md

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+---
+license: other
+language:
+- en
+---
+## Model Details
+This is an unofficial implementation of "[AlpaGasus: Training a better Alpaca with Fewer Data.](https://github.com/Lichang-Chen/AlpaGasus)" with [LLaMA2](https://huggingface.co/meta-llama/Llama-2-13b-hf) & QLoRA! Training code is available at our [repo](https://github.com/gauss5930/AlpaGasus2-QLoRA). 
+
+- **Developed by:** [Yunsang Yoo](https://huggingface.co/ryan0712) and [Hyunwoo Ko](https://huggingface.co/Cartinoe5930)
+- **Model type:** Auto-regressive model
+- **Language(s):** English
+- **Base Model:** [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf)
+- **License**: Non-Commercial Creative Commons license ([CC BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/))
+
+
+### Training dataset
+
+"StudentLLM/Alpagasus-2-13b-QLoRA-merged" used [gpt4life](https://github.com/gpt4life/alpagasus)'s gpt-3.5-turbo filtered dataset, 'alpaca_t45.json'.
+
+Configuration of the dataset is as follows:
+
+```
+{
+    'instruction': Give the instruction describing the question.
+    'input': Occasionally present, detailed instructions accompany the question if available.
+    'output': Give answers to questions.
+}
+.
+.
+.
+
+```
+
+### Prompt Template: Alpaca style prompt
+```
+Below is an instruction that describes a task. Write a response that appropriately completes the request.
+
+### Instruction:
+<prompt> (without the <>)
+
+### Input:
+<prompt> (if input exists)
+
+### Response:
+```
+
+### Fine-tuning Procedure
+Our model was finetuned using QLoRA on single A100 80GB GPU. Training details are described in [repo](https://github.com/gauss5930/AlpaGasus2-QLoRA).
+
+### Benchmark Metrics
+"StudentLLM/Alpagasus-2-13b-QLoRA-merged" model performance is uploaded on Huggingface's [OpenLLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). Model was evaluated on the tasks specified in HF's Open LLM Leaderboard(ARC, HellaSwag, MMLU, TruthfulQA).
+
+| Metric                | Value |
+|-----------------------|-------|
+| Avg.                  | 59.34 |
+| MMLU                  | 55.27 |
+| ARC                   | 61.09 |
+| HellaSwag             | 82.46 |
+| TruthfulQA            | 38.53 |
+
+### LLM Evaluation
+We tried to follow the evaluation metric introduced by the AlpaGasus paper. During the process, we consulted the code by [gpt4life](https://github.com/gpt4life/alpagasus). We used OpenAI's gpt-3.5-turbo as the evaluator model, and Alpaca2-LoRA-13B(it doesn't exist now...) as the comparison model. For more detailed information, please refer to our Github [repo](https://github.com/gauss5930/AlpaGasus2-QLoRA).
+
+The evaluation result of AlpaGasus2-QLoRA is as follows:
+![results](https://user-images.githubusercontent.com/80087878/262848860-8742bcc4-1bbc-449f-8bcf-660c08fcc10d.png)
+
+### How to use
+To use "StudentLLM/Alpagasus-2-13b-QLoRA-merged", please follow the following code! The use of the 7B model is the same!
+```python
+from peft import PeftModel, PeftConfig
+from transformers import AutoModelForCausalLM
+import torch
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+config = PeftConfig.from_pretrained("StudentLLM/Alpagasus-2-13B-QLoRA")
+model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-13b-hf", use_auth_token="yotu_HuggingFace_token").to(device)
+model = PeftModel.from_pretrained(model, "StudentLLM/Alpagasus-2-13B-QLoRA")
+
+tokenizer = AutoTokenizer.from_pretrained("StudentLLM/Alpagasus-2-13B-QLoRA")
+tokenizer.pad_token = tokenizer.eos_token
+
+input_data = "Please tell me 3 ways to relieve stress."   # You can enter any questions!!
+
+model_inputs = tokenizer(input_data, return_tensors='pt').to(device)
+model_output = model.generate(**model_inputs, max_length=256)
+model_output = tokenizer.decode(model_output[0], skip_special_tokens=True)
+print(model_output)
+```
+
+### Citations
+```bibtex
+@article{chen2023alpagasus,
+  title={AlpaGasus: Training a Better Alpaca with Fewer Data},
+  author={Lichang Chen, Shiyang Li, Jun Yan, Hai Wang, Kalpa Gunaratna, Vikas Yadav, Zheng Tang, Vijay Srinivasan, Tianyi Zhou, Heng Huang, Hongxia Jin},
+  journal={arXiv preprint arXiv:2307.08701},
+  year={2023}
+}
+```

config.json

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+{
+  "_name_or_path": "meta-llama/Llama-2-13b-hf",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 13824,
+  "max_position_embeddings": 4096,
+  "model_type": "llama",
+  "num_attention_heads": 40,
+  "num_hidden_layers": 40,
+  "num_key_value_heads": 40,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.32.1",
+  "use_cache": true,
+  "vocab_size": 32000
+}

generation_config.json

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+{
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 2,
+  "max_length": 4096,
+  "pad_token_id": 0,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.32.1"
+}

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+    "model.norm.weight": "pytorch_model-00003-of-00003.bin"
+  }
+}

special_tokens_map.json

@@ -0,0 +1,23 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,34 @@
+{
+  "bos_token": {
+    "__type": "AddedToken",
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "clean_up_tokenization_spaces": false,
+  "eos_token": {
+    "__type": "AddedToken",
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "legacy": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": null,
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": {
+    "__type": "AddedToken",
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "use_default_system_prompt": true
+}