Update with v2 model and config
Browse files- .gitattributes +1 -0
- README.md +8 -10
- config.json +5 -6
- pytorch_model.bin +1 -1
- special_tokens_map.json +2 -21
- tokenizer.model → tokenizer.json +2 -2
- tokenizer_config.json +0 -0
.gitattributes
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@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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nemo/*.nemo filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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nemo/*.nemo filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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@@ -5,7 +5,7 @@ license_link: >-
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https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf
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---
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# Minitron 8B Base
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Minitron is a family of small language models (SLMs) obtained by pruning NVIDIA's [Nemotron-4 15B](https://arxiv.org/abs/2402.16819) model. We prune model embedding size, attention heads, and MLP intermediate dimension, following which, we perform continued training with distillation to arrive at the final models.
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## HuggingFace Quickstart
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The [
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```
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git clone
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git checkout 63d9cb0
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pip install .
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```
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The following code provides an example of how to load the Minitron-8B model and use it to perform text generation.
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```python
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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# Load the tokenizer and model
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model_path = "nvidia/Minitron-8B-Base"
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tokenizer = AutoTokenizer.from_pretrained(model_path)
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device='cuda'
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| Average |
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| :---- |
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*Zero-shot performance.* Evaluated using select datasets from the [LM Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) with additions:
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HellaSwag | Winogrande | GSM8K| ARC-C | XLSum |
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| :------------- | :------------- | :------------- | :------------- | :------------- |
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*Code generation performance*. Evaluated using [HumanEval](https://github.com/openai/human-eval):
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https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf
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---
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# Nemotron-4 Minitron 8B Base
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Minitron is a family of small language models (SLMs) obtained by pruning NVIDIA's [Nemotron-4 15B](https://arxiv.org/abs/2402.16819) model. We prune model embedding size, attention heads, and MLP intermediate dimension, following which, we perform continued training with distillation to arrive at the final models.
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## HuggingFace Quickstart
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The [pull request](https://github.com/huggingface/transformers/pull/32495) to support this model in Hugging Face Transformers is under review and expected to be merged soon. In the meantime, please follow the installation instructions below:
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```
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$ git clone -b aot/head_dim_rope --single-branch https://github.com/suiyoubi/transformers.git && cd transformers
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$ pip install -e .
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```
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The following code provides an example of how to load the Nemotron-4-Minitron-8B model and use it to perform text generation.
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```python
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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# Load the tokenizer and model
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model_path = "nvidia/Nemotron-4-Minitron-8B-Base"
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tokenizer = AutoTokenizer.from_pretrained(model_path)
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device='cuda'
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| Average |
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| :---- |
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| 64.5 |
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*Zero-shot performance.* Evaluated using select datasets from the [LM Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) with additions:
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HellaSwag | Winogrande | GSM8K| ARC-C | XLSum |
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| :------------- | :------------- | :------------- | :------------- | :------------- |
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| 81.6 | 80.3 | 54.2 | 49.2 | 31.1
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*Code generation performance*. Evaluated using [HumanEval](https://github.com/openai/human-eval):
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config.json
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"model_type": "nemotron",
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"num_attention_heads": 48,
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"num_hidden_layers": 32,
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"kv_channels": 128,
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"num_key_value_heads": 8,
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"norm_eps": 1e-05,
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"rope_theta": 10000,
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"
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"rope_scaling": null,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.
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"use_cache": true,
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"vocab_size": 256000
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"model_type": "nemotron",
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"num_attention_heads": 48,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"norm_eps": 1e-05,
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"rope_theta": 10000,
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"partial_rotary_factor": 0.5,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.44.0",
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"use_cache": true,
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"vocab_size": 256000,
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"head_dim": 128
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}
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pytorch_model.bin
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size 16543512498
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size 16543512498
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special_tokens_map.json
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{
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"bos_token":
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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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},
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"eos_token": {
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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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},
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"unk_token": {
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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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}
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}
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{
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"bos_token": "<s>",
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"eos_token": "</s>"
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}
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tokenizer.model → tokenizer.json
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version https://git-lfs.github.com/spec/v1
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size
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size 18143149
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tokenizer_config.json
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