6c08917b88ddce7effa24944761208f129ddb9aa73459d0fe51e19489bb3ea2d
Browse files- README.md +85 -0
- config.json +38 -0
- generation_config.json +8 -0
- model-00002-of-00002.safetensors +3 -0
- model.safetensors.index.json +1114 -0
- smash_config.json +31 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1865 -0
README.md
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| 1 |
+
---
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| 2 |
+
thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
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| 3 |
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base_model: 01-ai/Yi-9B-200K
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metrics:
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- memory_disk
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| 6 |
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- memory_inference
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| 7 |
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- inference_latency
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| 8 |
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- inference_throughput
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| 9 |
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- inference_CO2_emissions
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| 10 |
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- inference_energy_consumption
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tags:
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- pruna-ai
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| 13 |
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---
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| 14 |
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<!-- header start -->
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<!-- 200823 -->
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| 16 |
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<div style="width: auto; margin-left: auto; margin-right: auto">
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<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
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| 18 |
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<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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| 19 |
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</a>
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</div>
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| 21 |
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<!-- header end -->
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| 22 |
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| 23 |
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[](https://twitter.com/PrunaAI)
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| 24 |
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[](https://github.com/PrunaAI)
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| 25 |
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[](https://www.linkedin.com/company/93832878/admin/feed/posts/?feedType=following)
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| 26 |
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[](https://discord.gg/rskEr4BZJx)
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# Simply make AI models cheaper, smaller, faster, and greener!
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| 29 |
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- Give a thumbs up if you like this model!
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| 31 |
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- Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact).
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| 32 |
+
- Request access to easily compress your *own* AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
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| 33 |
+
- Read the documentations to know more [here](https://pruna-ai-pruna.readthedocs-hosted.com/en/latest/)
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| 34 |
+
- Join Pruna AI community on Discord [here](https://discord.gg/CP4VSgck) to share feedback/suggestions or get help.
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| 35 |
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| 36 |
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## Results
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| 37 |
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| 40 |
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**Frequently Asked Questions**
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| 41 |
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- ***How does the compression work?*** The model is compressed with awq.
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| 42 |
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- ***How does the model quality change?*** The quality of the model output might vary compared to the base model.
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- ***How is the model efficiency evaluated?*** These results were obtained on HARDWARE_NAME with configuration described in `model/smash_config.json` and are obtained after a hardware warmup. The smashed model is directly compared to the original base model. Efficiency results may vary in other settings (e.g. other hardware, image size, batch size, ...). We recommend to directly run them in the use-case conditions to know if the smashed model can benefit you.
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- ***What is the model format?*** We use safetensors.
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| 45 |
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- ***What calibration data has been used?*** If needed by the compression method, we used WikiText as the calibration data.
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- ***What is the naming convention for Pruna Huggingface models?*** We take the original model name and append "turbo", "tiny", or "green" if the smashed model has a measured inference speed, inference memory, or inference energy consumption which is less than 90% of the original base model.
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| 47 |
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- ***How to compress my own models?*** You can request premium access to more compression methods and tech support for your specific use-cases [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
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| 48 |
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- ***What are "first" metrics?*** Results mentioning "first" are obtained after the first run of the model. The first run might take more memory or be slower than the subsequent runs due cuda overheads.
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| 49 |
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- ***What are "Sync" and "Async" metrics?*** "Sync" metrics are obtained by syncing all GPU processes and stop measurement when all of them are executed. "Async" metrics are obtained without syncing all GPU processes and stop when the model output can be used by the CPU. We provide both metrics since both could be relevant depending on the use-case. We recommend to test the efficiency gains directly in your use-cases.
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## Setup
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You can run the smashed model with these steps:
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| 54 |
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0. Check requirements from the original repo 01-ai/Yi-9B-200K installed. In particular, check python, cuda, and transformers versions.
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| 56 |
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1. Make sure that you have installed quantization related packages.
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| 57 |
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```bash
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| 58 |
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pip install autoawq
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| 59 |
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```
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| 60 |
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2. Load & run the model.
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| 61 |
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```python
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| 62 |
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from transformers import AutoModelForCausalLM, AutoTokenizer
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| 63 |
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from awq import AutoAWQForCausalLM
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| 64 |
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| 65 |
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model = AutoAWQForCausalLM.from_quantized("PrunaAI/01-ai-Yi-9B-200K-AWQ-4bit-smashed", trust_remote_code=True, device_map='auto')
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| 66 |
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tokenizer = AutoTokenizer.from_pretrained("01-ai/Yi-9B-200K")
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| 67 |
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| 68 |
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input_ids = tokenizer("What is the color of prunes?,", return_tensors='pt').to(model.device)["input_ids"]
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| 69 |
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outputs = model.generate(input_ids, max_new_tokens=216)
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| 71 |
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tokenizer.decode(outputs[0])
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| 72 |
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```
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| 73 |
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| 74 |
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## Configurations
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| 75 |
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The configuration info are in `smash_config.json`.
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## Credits & License
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| 79 |
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The license of the smashed model follows the license of the original model. Please check the license of the original model 01-ai/Yi-9B-200K before using this model which provided the base model. The license of the `pruna-engine` is [here](https://pypi.org/project/pruna-engine/) on Pypi.
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|
| 82 |
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## Want to compress other models?
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| 83 |
+
|
| 84 |
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- Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact).
|
| 85 |
+
- Request access to easily compress your own AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
|
config.json
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{
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"_name_or_path": "/ceph/hdd/staff/charpent/.cache/models051s_xeeeksgu4xr",
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| 3 |
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"architectures": [
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| 4 |
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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| 7 |
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"attention_dropout": 0.0,
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| 8 |
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"bos_token_id": 1,
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| 9 |
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"eos_token_id": 2,
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| 10 |
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"hidden_act": "silu",
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| 11 |
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"hidden_size": 4096,
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| 12 |
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"initializer_range": 0.02,
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| 13 |
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"intermediate_size": 11008,
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| 14 |
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"max_position_embeddings": 262144,
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| 15 |
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"mlp_bias": false,
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| 16 |
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"model_type": "llama",
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| 17 |
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"num_attention_heads": 32,
|
| 18 |
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"num_hidden_layers": 48,
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| 19 |
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"num_key_value_heads": 4,
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| 20 |
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"pad_token_id": 0,
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| 21 |
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"pretraining_tp": 1,
|
| 22 |
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"quantization_config": {
|
| 23 |
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"bits": 4,
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| 24 |
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"group_size": 128,
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| 25 |
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"modules_to_not_convert": null,
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| 26 |
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"quant_method": "awq",
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| 27 |
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"version": "gemm",
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| 28 |
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"zero_point": true
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| 29 |
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},
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| 30 |
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"rms_norm_eps": 1e-06,
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| 31 |
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"rope_scaling": null,
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| 32 |
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"rope_theta": 10000000.0,
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| 33 |
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"tie_word_embeddings": false,
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| 34 |
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"torch_dtype": "float16",
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| 35 |
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"transformers_version": "4.42.4",
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| 36 |
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"use_cache": false,
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| 37 |
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"vocab_size": 64000
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| 38 |
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}
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generation_config.json
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{
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| 2 |
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"_from_model_config": true,
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| 3 |
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"bos_token_id": 1,
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| 4 |
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"do_sample": true,
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| 5 |
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"eos_token_id": 2,
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| 6 |
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"pad_token_id": 0,
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| 7 |
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"transformers_version": "4.42.4"
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| 8 |
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}
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model-00002-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:c0b1ef0663d92b56ec4ee6a029d23943f36d998ede84daa326f84bfd8b86d581
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| 3 |
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size 524288128
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model.safetensors.index.json
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| 1 |
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"model.layers.46.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 1088 |
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"model.layers.47.self_attn.q_proj.qweight": "model-00001-of-00002.safetensors",
|
| 1089 |
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"model.layers.47.self_attn.q_proj.qzeros": "model-00001-of-00002.safetensors",
|
| 1090 |
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"model.layers.47.self_attn.q_proj.scales": "model-00001-of-00002.safetensors",
|
| 1091 |
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"model.layers.47.self_attn.k_proj.qweight": "model-00001-of-00002.safetensors",
|
| 1092 |
+
"model.layers.47.self_attn.k_proj.qzeros": "model-00001-of-00002.safetensors",
|
| 1093 |
+
"model.layers.47.self_attn.k_proj.scales": "model-00001-of-00002.safetensors",
|
| 1094 |
+
"model.layers.47.self_attn.v_proj.qweight": "model-00001-of-00002.safetensors",
|
| 1095 |
+
"model.layers.47.self_attn.v_proj.qzeros": "model-00001-of-00002.safetensors",
|
| 1096 |
+
"model.layers.47.self_attn.v_proj.scales": "model-00001-of-00002.safetensors",
|
| 1097 |
+
"model.layers.47.self_attn.o_proj.qweight": "model-00001-of-00002.safetensors",
|
| 1098 |
+
"model.layers.47.self_attn.o_proj.qzeros": "model-00001-of-00002.safetensors",
|
| 1099 |
+
"model.layers.47.self_attn.o_proj.scales": "model-00001-of-00002.safetensors",
|
| 1100 |
+
"model.layers.47.mlp.gate_proj.qweight": "model-00001-of-00002.safetensors",
|
| 1101 |
+
"model.layers.47.mlp.gate_proj.qzeros": "model-00001-of-00002.safetensors",
|
| 1102 |
+
"model.layers.47.mlp.gate_proj.scales": "model-00001-of-00002.safetensors",
|
| 1103 |
+
"model.layers.47.mlp.up_proj.qweight": "model-00001-of-00002.safetensors",
|
| 1104 |
+
"model.layers.47.mlp.up_proj.qzeros": "model-00001-of-00002.safetensors",
|
| 1105 |
+
"model.layers.47.mlp.up_proj.scales": "model-00001-of-00002.safetensors",
|
| 1106 |
+
"model.layers.47.mlp.down_proj.qweight": "model-00001-of-00002.safetensors",
|
| 1107 |
+
"model.layers.47.mlp.down_proj.qzeros": "model-00001-of-00002.safetensors",
|
| 1108 |
+
"model.layers.47.mlp.down_proj.scales": "model-00001-of-00002.safetensors",
|
| 1109 |
+
"model.layers.47.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 1110 |
+
"model.layers.47.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 1111 |
+
"model.norm.weight": "model-00001-of-00002.safetensors",
|
| 1112 |
+
"lm_head.weight": "model-00002-of-00002.safetensors"
|
| 1113 |
+
}
|
| 1114 |
+
}
|
smash_config.json
ADDED
|
@@ -0,0 +1,31 @@
|
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|
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|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"api_key": null,
|
| 3 |
+
"verify_url": "http://johnrachwan.pythonanywhere.com",
|
| 4 |
+
"smash_config": {
|
| 5 |
+
"pruners": "None",
|
| 6 |
+
"pruning_ratio": 0.0,
|
| 7 |
+
"factorizers": "None",
|
| 8 |
+
"quantizers": "['awq']",
|
| 9 |
+
"weight_quantization_bits": 4,
|
| 10 |
+
"output_deviation": 0.005,
|
| 11 |
+
"compilers": "None",
|
| 12 |
+
"static_batch": true,
|
| 13 |
+
"static_shape": true,
|
| 14 |
+
"controlnet": "None",
|
| 15 |
+
"unet_dim": 4,
|
| 16 |
+
"device": "cuda",
|
| 17 |
+
"cache_dir": "/ceph/hdd/staff/charpent/.cache/models051s_xee",
|
| 18 |
+
"batch_size": 1,
|
| 19 |
+
"model_name": "01-ai/Yi-9B-200K",
|
| 20 |
+
"task": "text_text_generation",
|
| 21 |
+
"max_batch_size": 1,
|
| 22 |
+
"qtype_weight": "torch.qint8",
|
| 23 |
+
"qtype_activation": "torch.quint8",
|
| 24 |
+
"qobserver": "<class 'torch.ao.quantization.observer.MinMaxObserver'>",
|
| 25 |
+
"qscheme": "torch.per_tensor_symmetric",
|
| 26 |
+
"qconfig": "x86",
|
| 27 |
+
"group_size": 128,
|
| 28 |
+
"damp_percent": 0.1,
|
| 29 |
+
"save_load_fn": "hf-awq"
|
| 30 |
+
}
|
| 31 |
+
}
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,30 @@
|
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|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": {
|
| 3 |
+
"content": "<|startoftext|>",
|
| 4 |
+
"lstrip": false,
|
| 5 |
+
"normalized": false,
|
| 6 |
+
"rstrip": false,
|
| 7 |
+
"single_word": false
|
| 8 |
+
},
|
| 9 |
+
"eos_token": {
|
| 10 |
+
"content": "<|endoftext|>",
|
| 11 |
+
"lstrip": false,
|
| 12 |
+
"normalized": false,
|
| 13 |
+
"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"pad_token": {
|
| 17 |
+
"content": "<unk>",
|
| 18 |
+
"lstrip": false,
|
| 19 |
+
"normalized": false,
|
| 20 |
+
"rstrip": false,
|
| 21 |
+
"single_word": false
|
| 22 |
+
},
|
| 23 |
+
"unk_token": {
|
| 24 |
+
"content": "<unk>",
|
| 25 |
+
"lstrip": false,
|
| 26 |
+
"normalized": false,
|
| 27 |
+
"rstrip": false,
|
| 28 |
+
"single_word": false
|
| 29 |
+
}
|
| 30 |
+
}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,1865 @@
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|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
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"add_eos_token": false,
|
| 4 |
+
"add_prefix_space": null,
|
| 5 |
+
"added_tokens_decoder": {
|
| 6 |
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"0": {
|
| 7 |
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|
| 8 |
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"lstrip": false,
|
| 9 |
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"normalized": false,
|
| 10 |
+
"rstrip": false,
|
| 11 |
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"single_word": false,
|
| 12 |
+
"special": true
|
| 13 |
+
},
|
| 14 |
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"1": {
|
| 15 |
+
"content": "<|startoftext|>",
|
| 16 |
+
"lstrip": false,
|
| 17 |
+
"normalized": false,
|
| 18 |
+
"rstrip": false,
|
| 19 |
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"single_word": false,
|
| 20 |
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"special": true
|
| 21 |
+
},
|
| 22 |
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"2": {
|
| 23 |
+
"content": "<|endoftext|>",
|
| 24 |
+
"lstrip": false,
|
| 25 |
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"normalized": false,
|
| 26 |
+
"rstrip": false,
|
| 27 |
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"single_word": false,
|
| 28 |
+
"special": true
|
| 29 |
+
},
|
| 30 |
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"6": {
|
| 31 |
+
"content": "<|im_start|>",
|
| 32 |
+
"lstrip": false,
|
| 33 |
+
"normalized": false,
|
| 34 |
+
"rstrip": false,
|
| 35 |
+
"single_word": false,
|
| 36 |
+
"special": true
|
| 37 |
+
},
|
| 38 |
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"7": {
|
| 39 |
+
"content": "<|im_end|>",
|
| 40 |
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"lstrip": false,
|
| 41 |
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"normalized": false,
|
| 42 |
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"rstrip": false,
|
| 43 |
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"single_word": false,
|
| 44 |
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"special": true
|
| 45 |
+
},
|
| 46 |
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"8": {
|
| 47 |
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"content": "<|im_sep|>",
|
| 48 |
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"lstrip": false,
|
| 49 |
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|
| 50 |
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|
| 51 |
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|
| 52 |
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"special": true
|
| 53 |
+
},
|
| 54 |
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"14": {
|
| 55 |
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"content": "<fim_prefix>",
|
| 56 |
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"lstrip": false,
|
| 57 |
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"normalized": false,
|
| 58 |
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"rstrip": false,
|
| 59 |
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|
| 60 |
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"special": true
|
| 61 |
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| 62 |
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"15": {
|
| 63 |
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|
| 64 |
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| 65 |
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| 66 |
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|
| 67 |
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| 68 |
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"special": true
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| 69 |
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|
| 70 |
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"16": {
|
| 71 |
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"content": "<fim_suffix>",
|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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"special": true
|
| 77 |
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|
| 78 |
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"17": {
|
| 79 |
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"content": "<fim_pad>",
|
| 80 |
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|
| 81 |
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| 82 |
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| 83 |
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| 84 |
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|
| 85 |
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| 86 |
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"18": {
|
| 87 |
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"content": "<filename>",
|
| 88 |
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|
| 89 |
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|
| 90 |
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|
| 91 |
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| 92 |
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"special": true
|
| 93 |
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|
| 94 |
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"19": {
|
| 95 |
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"content": "<gh_stars>",
|
| 96 |
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"lstrip": false,
|
| 97 |
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|
| 98 |
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|
| 99 |
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|
| 100 |
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"special": true
|
| 101 |
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| 102 |
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"20": {
|
| 103 |
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"content": "<issue_start>",
|
| 104 |
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|
| 105 |
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|
| 106 |
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|
| 107 |
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|
| 108 |
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"special": true
|
| 109 |
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|
| 110 |
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|
| 111 |
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|
| 112 |
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|
| 113 |
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|
| 114 |
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|
| 115 |
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|
| 116 |
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"special": true
|
| 117 |
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| 118 |
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"22": {
|
| 119 |
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|
| 120 |
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|
| 121 |
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|
| 122 |
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|
| 123 |
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| 124 |
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|
| 125 |
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| 126 |
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|
| 127 |
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|
| 128 |
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|
| 129 |
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|
| 130 |
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| 131 |
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| 132 |
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| 133 |
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| 134 |
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"24": {
|
| 135 |
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"content": "<jupyter_text>",
|
| 136 |
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|
| 137 |
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|
| 138 |
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|
| 139 |
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|
| 140 |
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"special": true
|
| 141 |
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|
| 142 |
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"25": {
|
| 143 |
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"content": "<jupyter_code>",
|
| 144 |
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|
| 145 |
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|
| 146 |
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|
| 147 |
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|
| 148 |
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"special": true
|
| 149 |
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|
| 150 |
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"26": {
|
| 151 |
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"content": "<jupyter_output>",
|
| 152 |
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|
| 153 |
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|
| 154 |
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|
| 155 |
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|
| 156 |
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"special": true
|
| 157 |
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|
| 158 |
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"27": {
|
| 159 |
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"content": "<empty_output>",
|
| 160 |
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"lstrip": false,
|
| 161 |
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|
| 162 |
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|
| 163 |
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|
| 164 |
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"special": true
|
| 165 |
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|
| 166 |
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"28": {
|
| 167 |
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"content": "<commit_before>",
|
| 168 |
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|
| 169 |
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|
| 170 |
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|
| 171 |
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|
| 172 |
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|
| 173 |
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|
| 174 |
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"29": {
|
| 175 |
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"content": "<commit_msg>",
|
| 176 |
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"lstrip": false,
|
| 177 |
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|
| 178 |
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|
| 179 |
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|
| 180 |
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"special": true
|
| 181 |
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|
| 182 |
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"30": {
|
| 183 |
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"content": "<commit_after>",
|
| 184 |
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|
| 185 |
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|
| 186 |
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|
| 187 |
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|
| 188 |
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|
| 189 |
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|
| 190 |
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|
| 191 |
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|
| 192 |
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|
| 193 |
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|
| 194 |
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|
| 195 |
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|
| 196 |
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"special": true
|
| 197 |
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|
| 198 |
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"32": {
|
| 199 |
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"content": "<h1>",
|
| 200 |
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|
| 201 |
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|
| 202 |
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|
| 203 |
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|
| 204 |
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|
| 205 |
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|
| 206 |
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|
| 207 |
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"content": "<h1/>",
|
| 208 |
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|
| 209 |
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|
| 210 |
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|
| 211 |
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|
| 212 |
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|
| 213 |
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|
| 214 |
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|
| 215 |
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|
| 216 |
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|
| 217 |
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|
| 218 |
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|
| 219 |
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| 220 |
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| 221 |
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| 222 |
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|
| 223 |
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| 224 |
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|
| 225 |
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|
| 226 |
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|
| 227 |
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| 228 |
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| 229 |
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| 230 |
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|
| 231 |
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| 232 |
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| 233 |
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| 234 |
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| 235 |
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| 236 |
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| 237 |
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| 238 |
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|
| 239 |
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| 240 |
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| 241 |
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| 245 |
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| 246 |
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| 247 |
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| 248 |
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| 249 |
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