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- README.md +84 -0
- mlc-chat-config.json +37 -0
- ndarray-cache.json +3032 -0
- params_shard_0.bin +3 -0
- params_shard_1.bin +3 -0
- params_shard_10.bin +3 -0
- params_shard_11.bin +3 -0
- params_shard_12.bin +3 -0
- params_shard_13.bin +3 -0
- params_shard_14.bin +3 -0
- params_shard_15.bin +3 -0
- params_shard_16.bin +3 -0
- params_shard_17.bin +3 -0
- params_shard_18.bin +3 -0
- params_shard_19.bin +3 -0
- params_shard_2.bin +3 -0
- params_shard_20.bin +3 -0
- params_shard_21.bin +3 -0
- params_shard_22.bin +3 -0
- params_shard_23.bin +3 -0
- params_shard_24.bin +3 -0
- params_shard_25.bin +3 -0
- params_shard_26.bin +3 -0
- params_shard_27.bin +3 -0
- params_shard_28.bin +3 -0
- params_shard_29.bin +3 -0
- params_shard_3.bin +3 -0
- params_shard_30.bin +3 -0
- params_shard_31.bin +3 -0
- params_shard_32.bin +3 -0
- params_shard_33.bin +3 -0
- params_shard_34.bin +3 -0
- params_shard_35.bin +3 -0
- params_shard_36.bin +3 -0
- params_shard_37.bin +3 -0
- params_shard_38.bin +3 -0
- params_shard_39.bin +3 -0
- params_shard_4.bin +3 -0
- params_shard_40.bin +3 -0
- params_shard_41.bin +3 -0
- params_shard_42.bin +3 -0
- params_shard_43.bin +3 -0
- params_shard_44.bin +3 -0
- params_shard_45.bin +3 -0
- params_shard_46.bin +3 -0
- params_shard_47.bin +3 -0
- params_shard_48.bin +3 -0
- params_shard_49.bin +3 -0
- params_shard_5.bin +3 -0
- params_shard_50.bin +3 -0
README.md
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| 1 |
+
---
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| 2 |
+
license: apache-2.0
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+
language:
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- en
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- zh
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+
library_name: transformers
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widget:
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- text: "<s> [|User|] Hi 👋 </s>[|Assistant|]"
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---
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+
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+
*NOTE: This is the MLC-LLM version of the following model*
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## MiniChat-3B
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📑 [arXiv](https://arxiv.org/abs/2311.07052) | 👻 [GitHub](https://github.com/GeneZC/MiniMA) | 🤗 [HuggingFace-MiniMA](https://huggingface.co/GeneZC/MiniMA-3B) | 🤗 [HuggingFace-MiniChat](https://huggingface.co/GeneZC/MiniChat-3B) | 🤗 [HuggingFace-MiniChat-1.5](https://huggingface.co/GeneZC/MiniChat-1.5-3B) | 🤖 [ModelScope-MiniMA](https://modelscope.cn/models/GeneZC/MiniMA-3B) | 🤖 [ModelScope-MiniChat](https://modelscope.cn/models/GeneZC/MiniChat-3B)
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🆕 **Updates: MiniChat-1.5-3B**
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❗ Must comply with LICENSE of LLaMA2 since it is derived from LLaMA2.
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A language model distilled and finetuned from an adapted version of LLaMA2-7B following "Towards the Law of Capacity Gap in Distilling Language Models".
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Outperforming a wide range of 3B competitors in GPT4 evaluation and even competing with several 7B chat models.
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<img src="./teaser_b.jpg" alt="teaser_b" width="687" />
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The following is an example code snippet to use MiniChat-3B:
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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from conversation import get_default_conv_template
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# MiniChat
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tokenizer = AutoTokenizer.from_pretrained("GeneZC/MiniChat-3B", use_fast=False)
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# GPU.
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model = AutoModelForCausalLM.from_pretrained("GeneZC/MiniChat-3B", use_cache=True, device_map="auto", torch_dtype=torch.float16).eval()
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# CPU.
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# model = AutoModelForCausalLM.from_pretrained("GeneZC/MiniChat-3B", use_cache=True, device_map="cpu", torch_dtype=torch.float32).eval()
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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conv = get_default_conv_template("minichat")
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question = "Implement a program to find the common elements in two arrays without using any extra data structures."
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conv.append_message(conv.roles[0], question)
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conv.append_message(conv.roles[1], None)
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prompt = conv.get_prompt()
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input_ids = tokenizer([prompt]).input_ids
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output_ids = model.generate(
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torch.as_tensor(input_ids).to(device),
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do_sample=True,
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temperature=0.7,
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max_new_tokens=1024,
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)
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output_ids = output_ids[0][len(input_ids[0]):]
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output = tokenizer.decode(output_ids, skip_special_tokens=True).strip()
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# output: "def common_elements(arr1, arr2):\n if len(arr1) == 0:\n return []\n if len(arr2) == 0:\n return arr1\n\n common_elements = []\n for element in arr1:\n if element in arr2:\n common_elements.append(element)\n\n return common_elements"
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# Multiturn conversation could be realized by continuously appending questions to `conv`.
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| 60 |
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```
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| 61 |
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## Bibtex
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| 63 |
+
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| 64 |
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```bibtex
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| 65 |
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@article{zhang2023law,
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title={Towards the Law of Capacity Gap in Distilling Language Models},
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author={Zhang, Chen and Song, Dawei and Ye, Zheyu and Gao, Yan},
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year={2023},
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url={https://arxiv.org/abs/2311.07052}
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}
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```
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_GeneZC__MiniChat-3B)
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| Metric | Value |
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|-----------------------|---------------------------|
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| Avg. | 42.94 |
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| 78 |
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| ARC (25-shot) | 44.03 |
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| 79 |
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| HellaSwag (10-shot) | 67.19 |
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| MMLU (5-shot) | 39.17 |
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| 81 |
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| TruthfulQA (0-shot) | 45.67 |
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| 82 |
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| Winogrande (5-shot) | 65.27 |
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| GSM8K (5-shot) | 10.54 |
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| DROP (3-shot) | 28.73 |
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mlc-chat-config.json
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{
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"model_lib": "MiniChat-3B-q4f16_1",
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"local_id": "MiniChat-3B-q4f16_1",
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"estimated_vram_req": 2200000000,
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"conv_config": {
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"seps": ["</s>"],
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"stop_tokens": [ 2 ],
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"offset": 0,
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"separator_style": 0,
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"messages": [
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],
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"stop_str": "</s>",
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"roles": [ "[|User|]", "[|Assistant|]" ],
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"role_msg_sep": ": ",
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"role_empty_sep": "\n",
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"system": "",
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"add_bos": true,
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"bos": "<s>",
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"eos": "</s>",
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"prefix_tokens": [],
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"name": "chatml2"
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},
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"temperature": 0.7,
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"repetition_penalty": 1.0,
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"top_p": 0.95,
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"mean_gen_len": 128,
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"max_gen_len": 512,
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"max_window_size": 2048,
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"num_shards": 1,
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"shift_fill_factor": 0.3,
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"tokenizer_files": [
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"tokenizer.model"
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],
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"model_category": "llama",
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"model_name": "MiniChat-3B",
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"vocab_size": 49216
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}
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ndarray-cache.json
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| 1 |
+
{
|
| 2 |
+
"metadata": {
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| 3 |
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"ParamSize": 247
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| 4 |
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},
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| 5 |
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"records": [
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| 6 |
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{
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| 7 |
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"dataPath": "params_shard_0.bin",
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| 8 |
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"format": "raw-shard",
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| 9 |
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"nbytes": 75595776,
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| 10 |
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"records": [
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| 11 |
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{
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| 12 |
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"name": "param_0",
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| 13 |
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"shape": [
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| 14 |
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| 15 |
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384
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| 16 |
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],
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| 17 |
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"dtype": "uint32",
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| 18 |
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"format": "raw",
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| 19 |
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"nbytes": 75595776,
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| 20 |
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"byteOffset": 0
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| 22 |
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| 23 |
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},
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| 24 |
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{
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| 25 |
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"dataPath": "params_shard_1.bin",
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