Commit
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Parent(s):
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ExLLaMA V2 quant of Yi-6B-200K-8.0bpw-h8-exl2
Browse files- README.md +94 -0
- config.json +29 -0
- generation_config.json +7 -0
- model.safetensors.index.json +298 -0
- output.safetensors +3 -0
- pytorch_model.bin.index.json +298 -0
- tokenizer.model +3 -0
- tokenizer_config.json +9 -0
README.md
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---
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license: other
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license_name: yi-license
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license_link: LICENSE
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---
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<div align="center">
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<img src="./Yi.svg" width="200px">
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</div>
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## Introduction
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The **Yi** series models are large language models trained from scratch by
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developers at [01.AI](https://01.ai/). The first public release contains two
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bilingual(English/Chinese) base models with the parameter sizes of 6B([`Yi-6B`](https://huggingface.co/01-ai/Yi-6B))
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and 34B([`Yi-34B`](https://huggingface.co/01-ai/Yi-34B)). Both of them are trained
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with 4K sequence length and can be extended to 32K during inference time.
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The [`Yi-6B-200K`](https://huggingface.co/01-ai/Yi-6B-200K)
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and [`Yi-34B-200K`](https://huggingface.co/01-ai/Yi-34B-200K) are base model with
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200K context length.
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## News
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- 🎯 **2023/11/06**: The base model of [`Yi-6B-200K`](https://huggingface.co/01-ai/Yi-6B-200K)
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and [`Yi-34B-200K`](https://huggingface.co/01-ai/Yi-34B-200K) with 200K context length.
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- 🎯 **2023/11/02**: The base model of [`Yi-6B`](https://huggingface.co/01-ai/Yi-6B) and
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[`Yi-34B`](https://huggingface.co/01-ai/Yi-34B).
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## Model Performance
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| Model | MMLU | CMMLU | C-Eval | GAOKAO | BBH | Common-sense Reasoning | Reading Comprehension | Math & Code |
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| :------------ | :------: | :------: | :------: | :------: | :------: | :--------------------: | :-------------------: | :---------: |
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| | 5-shot | 5-shot | 5-shot | 0-shot | 3-shot@1 | - | - | - |
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| LLaMA2-34B | 62.6 | - | - | - | 44.1 | 69.9 | 68.0 | 26.0 |
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| LLaMA2-70B | 68.9 | 53.3 | - | 49.8 | 51.2 | 71.9 | 69.4 | 36.8 |
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| Baichuan2-13B | 59.2 | 62.0 | 58.1 | 54.3 | 48.8 | 64.3 | 62.4 | 23.0 |
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| Qwen-14B | 66.3 | 71.0 | 72.1 | 62.5 | 53.4 | 73.3 | 72.5 | **39.8** |
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| Skywork-13B | 62.1 | 61.8 | 60.6 | 68.1 | 41.7 | 72.4 | 61.4 | 24.9 |
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| InternLM-20B | 62.1 | 59.0 | 58.8 | 45.5 | 52.5 | 78.3 | - | 30.4 |
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| Aquila-34B | 67.8 | 71.4 | 63.1 | - | - | - | - | - |
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| Falcon-180B | 70.4 | 58.0 | 57.8 | 59.0 | 54.0 | 77.3 | 68.8 | 34.0 |
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| Yi-6B | 63.2 | 75.5 | 72.0 | 72.2 | 42.8 | 72.3 | 68.7 | 19.8 |
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| Yi-6B-200K | 64.0 | 75.3 | 73.5 | 73.9 | 42.0 | 72.0 | 69.1 | 19.0 |
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| **Yi-34B** | **76.3** | **83.7** | 81.4 | 82.8 | **54.3** | **80.1** | 76.4 | 37.1 |
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| Yi-34B-200K | 76.1 | 83.6 | **81.9** | **83.4** | 52.7 | 79.7 | **76.6** | 36.3 |
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While benchmarking open-source models, we have observed a disparity between the
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results generated by our pipeline and those reported in public sources (e.g.
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OpenCompass). Upon conducting a more in-depth investigation of this difference,
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we have discovered that various models may employ different prompts,
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post-processing strategies, and sampling techniques, potentially resulting in
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significant variations in the outcomes. Our prompt and post-processing strategy
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remains consistent with the original benchmark, and greedy decoding is employed
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during evaluation without any post-processing for the generated content. For
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scores that were not reported by the original authors (including scores reported
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with different settings), we try to get results with our pipeline.
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To evaluate the model's capability extensively, we adopted the methodology
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outlined in Llama2. Specifically, we included PIQA, SIQA, HellaSwag, WinoGrande,
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ARC, OBQA, and CSQA to assess common sense reasoning. SquAD, QuAC, and BoolQ
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were incorporated to evaluate reading comprehension. CSQA was exclusively tested
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using a 7-shot setup, while all other tests were conducted with a 0-shot
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configuration. Additionally, we introduced GSM8K (8-shot@1), MATH (4-shot@1),
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HumanEval (0-shot@1), and MBPP (3-shot@1) under the category "Math & Code". Due
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to technical constraints, we did not test Falcon-180 on QuAC and OBQA; the score
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is derived by averaging the scores on the remaining tasks. Since the scores for
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these two tasks are generally lower than the average, we believe that
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Falcon-180B's performance was not underestimated.
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## Usage
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Please visit our [github repository](https://github.com/01-ai/Yi) for general
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guidance on how to use this model.
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## Disclaimer
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Although we use data compliance checking algorithms during the training process
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to ensure the compliance of the trained model to the best of our ability, due to
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the complexity of the data and the diversity of language model usage scenarios,
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we cannot guarantee that the model will generate correct and reasonable output
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in all scenarios. Please be aware that there is still a risk of the model
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producing problematic outputs. We will not be responsible for any risks and
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issues resulting from misuse, misguidance, illegal usage, and related
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misinformation, as well as any associated data security concerns.
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## License
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The Yi series models are fully open for academic research and free commercial
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usage with permission via applications. All usage must adhere to the [Model
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License Agreement 2.0](https://huggingface.co/01-ai/Yi-6B-200K/blob/main/LICENSE). To
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apply for the official commercial license, please contact us
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([yi@01.ai](mailto:yi@01.ai)).
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config.json
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{
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"architectures": [
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"YiForCausalLM"
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],
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"auto_map": {
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"AutoConfig": "configuration_yi.YiConfig",
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"AutoModel": "modeling_yi.YiModel",
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"AutoModelForCausalLM":"modeling_yi.YiForCausalLM"
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},
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 11008,
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"max_position_embeddings": 200000,
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"model_type": "Yi",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 4,
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"pad_token_id": 0,
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"rms_norm_eps": 1e-05,
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"rope_theta": 5000000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.34.0",
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"use_cache": true,
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"vocab_size": 64000
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"pad_token_id": 0,
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"transformers_version": "4.31.0"
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}
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model.safetensors.index.json
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tokenizer.model
ADDED
@@ -0,0 +1,3 @@
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|
1 |
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version https://git-lfs.github.com/spec/v1
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size 1033105
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tokenizer_config.json
ADDED
@@ -0,0 +1,9 @@
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|
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|
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|
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|
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|
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{
|
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"auto_map": {
|
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"AutoTokenizer": ["tokenization_yi.YiTokenizer", null]
|
4 |
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|
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"add_bos_token": false,
|
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|
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"model_max_length": 200000,
|
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|
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