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Model: neuralmagic/SparseLLama-2-7b-ultrachat_200k-pruned_50.2of4 Source: Original Platform
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README.md
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README.md
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---
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datasets:
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- HuggingFaceH4/ultrachat_200k
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language:
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- en
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pipeline_tag: text-generation
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---
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# SparseLlama-2-7b-ultrachat_200k-pruned_50.2of4
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## Model Overview
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- **Model Architecture:** Llama-2
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- **Input:** Text
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- **Output:** Text
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- **Model Optimizations:**
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- **Pruned:** 50% 2:4
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- **Release Date:** 6/28/2024
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- **Version:** 1.0
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- **Model Developers:** Neural Magic
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Compressed version of [Llama-2-7b](https://huggingface.co/meta-llama/Llama-2-7b-hf) specialized for text-generation.
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This model was obtained by fine-tuning the Sparse Foundational model [Sparse-Llama-2-7b-pruned_50.2of4](https://huggingface.co/nm-testing/SparseLlama-2-7b-pruned_50.2of4) on the [ultrachat_200k](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k) dataset.
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It achieves a win rate of 62.1% on the [AlpacaEval](https://github.com/tatsu-lab/alpaca_eval) benchmark (version 1.0) when using [Llama-2-70b-chat](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf) as evaluator, whereas the dense [Llama-2-7b-ultrachat200k](https://huggingface.co/neuralmagic/Llama-2-7b-ultrachat200k) model achieves 57.6% win rate.
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This model was produced as part if Neural Magic's Sparse Foundational Models initiative, and demostrates the capability of Sparse Foundational Models to transfer to the text-generation domain.
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**Note:** This model uses the chat template from [zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta).
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## Model Optimizations
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This model is derived from the Sparse Foundational model [Sparse-Llama-2-7b-pruned_50.2of4](https://huggingface.co/nm-testing/SparseLlama-2-7b-pruned_50.2of4), which was obtained by applying the [SparseGPT](https://arxiv.org/abs/2301.00774) algorithm to prune [Llama-2-7b](https://huggingface.co/meta-llama/Llama-2-7b-hf) to 50% sparsity with a 2:4 mask.
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This optimization reduces the number of parameters by 50%, reducing the disk size and FLOPs by the same level.
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## Evaluation
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This model was evaluated in the [AlpacaEval](https://github.com/tatsu-lab/alpaca_eval) benchmark using [Llama-2-70b-chat](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf) as evaluator.
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## Accuracy
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| Model | Win rate | Recovery |
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| :----- | :--------: | :--------: |
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| [Llama-2-7b](https://huggingface.co/meta-llama/Llama-2-7b-hf) | 3.7% | -- |
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| [Llama-2-7b-ultrachat200k](https://huggingface.co/neuralmagic/Llama-2-7b-ultrachat200k) | 57.6% | -- |
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| SparseLlama-2-7b-ultrachat_200k-pruned_50.2of4 | 62.1% | 108% |
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28
special_tokens_map.json
Normal file
28
special_tokens_map.json
Normal file
@@ -0,0 +1,28 @@
|
||||
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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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|
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|
||||
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|
||||
93392
tokenizer.json
Normal file
93392
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
48
tokenizer_config.json
Normal file
48
tokenizer_config.json
Normal file
@@ -0,0 +1,48 @@
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{
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"add_bos_token": true,
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"add_eos_token": false,
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"add_prefix_space": null,
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"added_tokens_decoder": {
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"0": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"2": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"additional_special_tokens": [
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"<unk>",
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"<s>",
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"</s>"
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],
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"bos_token": "<s>",
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"chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n' + message['content'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }}\n{% endif %}\n{% endfor %}",
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"clean_up_tokenization_spaces": false,
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"eos_token": "</s>",
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"legacy": false,
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"model_max_length": 4096,
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"pad_token": null,
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"padding_side": "right",
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"sp_model_kwargs": {},
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": "<unk>",
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"use_default_system_prompt": true
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}
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