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- LICENSE +201 -0
- README.md +227 -3
- assets/Signiture_Trillion_BlackBG.png +3 -0
- assets/Signiture_Trillion_WhiteBG.png +3 -0
- assets/frontier.png +0 -0
- config.json +29 -0
- generation_config.json +8 -0
- model-00001-of-00004.safetensors +3 -0
- model-00002-of-00004.safetensors +3 -0
- model-00003-of-00004.safetensors +3 -0
- model-00004-of-00004.safetensors +3 -0
- model.safetensors.index.json +298 -0
- special_tokens_map.json +153 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1169 -0
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README.md
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|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- finetuned
|
| 5 |
+
- chat
|
| 6 |
+
language:
|
| 7 |
+
- en
|
| 8 |
+
- ko
|
| 9 |
+
- ja
|
| 10 |
+
- zh
|
| 11 |
+
pipeline_tag: text-generation
|
| 12 |
+
library_name: transformers
|
| 13 |
+
---
|
| 14 |
+
|
| 15 |
+
# Trillion-7B-preview
|
| 16 |
+
|
| 17 |
+
<p align="center">
|
| 18 |
+
<picture>
|
| 19 |
+
<source media="(prefers-color-scheme: dark)" srcset="assets/Signiture_Trillion_BlackBG.png", width="300", style="margin: 40 auto;">
|
| 20 |
+
<img src="assets/Signiture_Trillion_WhiteBG.png" alt="logo", width="300", style="margin: 40 auto;">
|
| 21 |
+
</picture>
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
## Introduction
|
| 25 |
+
|
| 26 |
+
We introduce Trillion-7B-preview, a preview of our latest large language model designed to push the boundaries of multilingual scalability and performance.
|
| 27 |
+
|
| 28 |
+
|
| 29 |
+
When comparing performance to training FLOPs for Trillion-7B-preview with competitive models, our model pushes the Pareto frontier, achieving ~66.5% average performance while using significantly fewer compute (~9.3×10²² FLOPs). It outperforms models like Mistral-7B-Instruct-v0.3 and SOLAR-10.7B-Instruct-v1.0 while remaining competitive with models requiring 3-8× more compute such as Qwen2.5-7B-Instruct and EXAONE-3.5-7.8B-Instruct. For full benchmark results, see tables below.
|
| 30 |
+
|
| 31 |
+
<p align="center">
|
| 32 |
+
<img src="assets/frontier.png" alt="Average Performance vs. Approximate Training FLOPs" width="700">
|
| 33 |
+
</p>
|
| 34 |
+
|
| 35 |
+
- Type: Causal Language Model
|
| 36 |
+
- Training Stage: Pre-training & Post-training
|
| 37 |
+
- Architecture: Transformer Decoder with RoPE, SwiGLU, RMSNorm
|
| 38 |
+
- Number of Parameters: 7.76B
|
| 39 |
+
- Number of Layers: 32
|
| 40 |
+
- Number of Attention Heads: 32
|
| 41 |
+
- Context Length: 4,096
|
| 42 |
+
- Number of Tokens seen: 2T
|
| 43 |
+
- Vocab Size: 128,128
|
| 44 |
+
|
| 45 |
+
|
| 46 |
+
## Quickstart
|
| 47 |
+
|
| 48 |
+
Here is a code snippet with `apply_chat_template` that demonstrates how to load the tokenizer and model and generate text.
|
| 49 |
+
|
| 50 |
+
```python
|
| 51 |
+
import torch
|
| 52 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer
|
| 53 |
+
|
| 54 |
+
model_name = "trillionlabs/Trillion-7B-preview"
|
| 55 |
+
|
| 56 |
+
model = AutoModelForCausalLM.from_pretrained(
|
| 57 |
+
model_name,
|
| 58 |
+
torch_dtype=torch.bfloat16,
|
| 59 |
+
device_map="auto"
|
| 60 |
+
)
|
| 61 |
+
tokenizer = AutoTokenizer.from_pretrained(model_name)
|
| 62 |
+
|
| 63 |
+
prompt = "Tell me a hilarious knock knock joke."
|
| 64 |
+
messages = [
|
| 65 |
+
{"role": "user", "content": prompt}
|
| 66 |
+
]
|
| 67 |
+
text = tokenizer.apply_chat_template(
|
| 68 |
+
messages,
|
| 69 |
+
tokenize=False,
|
| 70 |
+
add_generation_prompt=True
|
| 71 |
+
)
|
| 72 |
+
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
|
| 73 |
+
|
| 74 |
+
generated_ids = model.generate(
|
| 75 |
+
**model_inputs,
|
| 76 |
+
max_new_tokens=512
|
| 77 |
+
)
|
| 78 |
+
generated_ids = [
|
| 79 |
+
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
|
| 80 |
+
]
|
| 81 |
+
|
| 82 |
+
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
|
| 83 |
+
print(response)
|
| 84 |
+
|
| 85 |
+
"""
|
| 86 |
+
Sure! Here's a classic knock-knock joke that's guaranteed to make you chuckle:
|
| 87 |
+
Knock, knock.
|
| 88 |
+
Who's there?
|
| 89 |
+
Lettuce.
|
| 90 |
+
Lettuce who?
|
| 91 |
+
Lettuce in, it's too cold out here!
|
| 92 |
+
"""
|
| 93 |
+
```
|
| 94 |
+
|
| 95 |
+
## Evaluation
|
| 96 |
+
|
| 97 |
+
We selected a wide variety of benchmarks that evaluate general reasoning, knowledge recall, coding abilities, mathematical reasoning, and instruction following capabilities. We evaluated Trillion-7B-preview along with several leading large language models of similar size. Our model especially demonstrates strong performance on Korean benchmarks.
|
| 98 |
+
|
| 99 |
+
|
| 100 |
+
<details>
|
| 101 |
+
<summary> Full evaluation settings </summary>
|
| 102 |
+
|
| 103 |
+
| Benchmark | Language | Evaluation Setting | Metric |
|
| 104 |
+
|:----------|:---------|:------------------|:-------|
|
| 105 |
+
| **General Reasoning and Reading Comprehension** | | | |
|
| 106 |
+
| • HellaSwag | English | 0-shot | accuracy |
|
| 107 |
+
| • TruthfulQA_mc1 | English | 6-shot | accuracy |
|
| 108 |
+
| • TruthfulQA_mc2 | English | 6-shot | accuracy |
|
| 109 |
+
| • ARC:C | English | 0-shot | accuracy |
|
| 110 |
+
| • HAERAE | Korean | 3-shot | accuracy |
|
| 111 |
+
| • KoBEST | Korean | 5-shot | accuracy |
|
| 112 |
+
| • BBH | English | 0-shot, CoT | accuracy |
|
| 113 |
+
| • xwinograd_en | English | 0-shot | accuracy |
|
| 114 |
+
| • xwinograd_jp | Japanese | 0-shot | accuracy |
|
| 115 |
+
| • xwinograd_zh | Chinese | 0-shot | accuracy |
|
| 116 |
+
| **Knowledge Recall** | | | |
|
| 117 |
+
| • KMMLU | Korean | 5-shot | accuracy |
|
| 118 |
+
| • MMLU | English | 5-shot | accuracy |
|
| 119 |
+
| • Global-MMLU-Lite-en | English | 5-shot | accuracy |
|
| 120 |
+
| • Global-MMLU-Lite-ko | Korean | 5-shot | accuracy |
|
| 121 |
+
| • Global-MMLU-Lite-ja | Japanese | 5-shot | accuracy |
|
| 122 |
+
| • Global-MMLU-Lite-zh | Chinese | 5-shot | accuracy |
|
| 123 |
+
| **Coding** | | | |
|
| 124 |
+
| • HumanEval | English | 0-shot, CoT | pass@1 |
|
| 125 |
+
| • MBPP | English | 0-shot, CoT| pass@1 |
|
| 126 |
+
| **Mathematical Reasoning** | | | |
|
| 127 |
+
| • GSM8k | English | 0-shot, CoT | exact-match |
|
| 128 |
+
| • MATH | English | 0-shot, CoT | exact-match |
|
| 129 |
+
| • GPQA | English | 4-shot | accuracy |
|
| 130 |
+
| • HRM8k | Korean | 0-shot, CoT | exact-match |
|
| 131 |
+
| **Instruction Following and Chat** | | | |
|
| 132 |
+
| • IFEval | English | 0-shot | strict-average |
|
| 133 |
+
| • koIFEval* | Korean | 0-shot | strict-average |
|
| 134 |
+
| • MT-Bench** | English | LLM-as-a-judge (gpt-4o-2024-08-06) | LLM score |
|
| 135 |
+
| • KO-MT-Bench** | Korean | LLM-as-a-judge (gpt-4o-2024-08-06) | LLM score |
|
| 136 |
+
| • LogicKor** | Korean | LLM-as-a-judge (gpt-4o-2024-08-06) | LLM score |
|
| 137 |
+
|
| 138 |
+
- *Note that koIFEval is our in-house evaluation benchmark for assessing instruction-following capabilities in Korean.
|
| 139 |
+
- **Note that MT-Bench, KO-MT-Bench, and LogicKor use a 10-point scale.
|
| 140 |
+
|
| 141 |
+
</details>
|
| 142 |
+
|
| 143 |
+
### Benchmark Results
|
| 144 |
+
|
| 145 |
+
- Trillion-7B-preview
|
| 146 |
+
- [LGAI-EXAONE/EXAONE-3.5-7.8B-Instruct](https://huggingface.co/LGAI-EXAONE/EXAONE-3.5-7.8B-Instruct)
|
| 147 |
+
- [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it)
|
| 148 |
+
- [meta-llama/Llama-3.1-8B-Instruct](meta-llama/Llama-3.1-8B-Instruct)
|
| 149 |
+
- [Qwen/Qwen2.5-7B-Instruct](Qwen/Qwen2.5-7B-Instruct)
|
| 150 |
+
- [upstage/SOLAR-10.7B-Instruct-v1.0](upstage/SOLAR-10.7B-Instruct-v1.0)
|
| 151 |
+
- [mistralai/Mistral-7B-Instruct-v0.3](mistralai/Mistral-7B-Instruct-v0.3)
|
| 152 |
+
|
| 153 |
+
|
| 154 |
+
### General Reasoning and Factuality
|
| 155 |
+
|
| 156 |
+
| Benchmark | Trillion-7B-preview | EXAONE-3.5-7.8B-Instruct | gemma-2-9b-it | Llama-3.1-8B-Instruct | Qwen2.5-7B-Instruct | SOLAR-10.7B-Instruct-v1.0 | Mistral-7B-Instruct-v0.3 |
|
| 157 |
+
| --- | --- | --- | --- | --- | --- | --- | --- |
|
| 158 |
+
| HellaSwag | 58.94 | 60.04 | 59.72 | 59.81 | 61.97 | 68.72 | 65.79 |
|
| 159 |
+
| TruthfulQA_mc1 | 36.10 | 40.64 | 42.96 | 38.07 | 47.74 | 56.18 | 42.47 |
|
| 160 |
+
| TruthfulQA_mc2 | 54.10 | 59.74 | 60.09 | 54.54 | 64.72 | 70.64 | 59.41 |
|
| 161 |
+
| ARC:C | 54.44 | 56.40 | 62.97 | 53.58 | 52.99 | 60.07 | 58.11 |
|
| 162 |
+
| HAERAE | 80.02 | 76.08 | 68.01 | 63.15 | 65.17 | 60.86 | 47.75 |
|
| 163 |
+
| KoBEST | 79.61 | 78.57 | 79.98 | 70.09 | 79.24 | 75.20 | 66.50 |
|
| 164 |
+
| KMMLU | 48.09 | 45.39 | 46.66 | 41.41 | 50.15 | 41.66 | 33.59 |
|
| 165 |
+
| MMLU | 63.52 | 65.65 | 72.24 | 68.32 | 74.23 | 65.20 | 61.84 |
|
| 166 |
+
| Global-MMLU-Lite-en | 67.75 | 69.50 | 76.25 | 67.50 | 77.25 | 71.75 | 65.50 |
|
| 167 |
+
| Global-MMLU-Lite-ko | 60.75 | 60.00 | 64.25 | 54.00 | 59.25 | 53.75 | 43.00 |
|
| 168 |
+
| Global-MMLU-Lite-ja | 60.75 | 45.75 | 66.50 | 54.50 | 65.75 | 50.75 | 50.00 |
|
| 169 |
+
| Global-MMLU-Lite-zh | 59.50 | 50.00 | 63.75 | 60.25 | 68.75 | 57.00 | 47.25 |
|
| 170 |
+
| BBH | 41.94 | 53.30 | 28.77 | 43.16 | 53.68 | 52.91 | 45.09 |
|
| 171 |
+
| xwinograd_en | 87.78 | 87.10 | 89.55 | 88.09 | 85.63 | 87.35 | 88.39 |
|
| 172 |
+
| xwinograd_jp | 79.98 | 74.45 | 80.92 | 76.02 | 72.89 | 72.58 | 70.70 |
|
| 173 |
+
| xwinograd_zh | 73.81 | 69.44 | 68.06 | 76.19 | 81.55 | 74.60 | 71.83 |
|
| 174 |
+
|
| 175 |
+
### Coding
|
| 176 |
+
|
| 177 |
+
| Benchmark | Trillion-7B-preview | EXAONE-3.5-7.8B-Instruct | gemma-2-9b-it | Llama-3.1-8B-Instruct | Qwen2.5-7B-Instruct | SOLAR-10.7B-Instruct-v1.0 | Mistral-7B-Instruct-v0.3 |
|
| 178 |
+
| --- | --- | --- | --- | --- | --- | --- | --- |
|
| 179 |
+
| HumanEval | 55.48 | 79.26 | 60.98 | 67.68 | 81.71 | 34.76 | 36.59 |
|
| 180 |
+
| MBPP | 40.40 | 61.40 | 8.40 | 39.20 | 51.00 | 29.40 | 36.00 |
|
| 181 |
+
|
| 182 |
+
### Mathematical Reasoning
|
| 183 |
+
|
| 184 |
+
| Benchmark | Trillion-7B-preview | EXAONE-3.5-7.8B-Instruct | gemma-2-9b-it | Llama-3.1-8B-Instruct | Qwen2.5-7B-Instruct | SOLAR-10.7B-Instruct-v1.0 | Mistral-7B-Instruct-v0.3 |
|
| 185 |
+
| --- | --- | --- | --- | --- | --- | --- | --- |
|
| 186 |
+
| GSM8k | 72.25 | 87.79 | 73.69 | 74.98 | 88.86 | 62.93 | 35.94 |
|
| 187 |
+
| MATH | 32.70 | 70.68 | - | 38.30 | 71.50 | 14.38 | 12.12 |
|
| 188 |
+
| GPQA | 32.81 | 38.61 | 36.83 | 30.58 | 34.15 | 28.35 | 32.59 |
|
| 189 |
+
| HRM8k | 30.10 | 38.99 | 16.04 | - | 41.51 | 20.68 | 7.89 |
|
| 190 |
+
|
| 191 |
+
### Instruction Following and Chat
|
| 192 |
+
|
| 193 |
+
| Benchmark | Trillion-7B-preview | EXAONE-3.5-7.8B-Instruct | gemma-2-9b-it | Llama-3.1-8B-Instruct | Qwen2.5-7B-Instruct | SOLAR-10.7B-Instruct-v1.0 | Mistral-7B-Instruct-v0.3 |
|
| 194 |
+
| --- | --- | --- | --- | --- | --- | --- | --- |
|
| 195 |
+
| IFEval | 79.13 | 81.42 | 75.48 | 74.93 | 75.85 | 51.61 | 52.64 |
|
| 196 |
+
| koIFEval | 66.58 | 54.65 | 43.30 | 36.07 | 48.55 | 26.12 | 34.22 |
|
| 197 |
+
| MT-Bench | 6.53 | 6.75 | - | 6.32 | 7.86 | 6.76 | 6.84 |
|
| 198 |
+
| KO-MT-Bench | 6.21 | 6.70 | - | 4.27 | 6.47 | 5.57 | 4.59 |
|
| 199 |
+
| LogicKor | 8.14 | 9.25 | 8.33 | 6.45 | 7.99 | 1.85 | 4.76
|
| 200 |
+
|
| 201 |
+
|
| 202 |
+
|
| 203 |
+
|
| 204 |
+
## Limitations
|
| 205 |
+
|
| 206 |
+
- Language Support: The model is optimized for English, Korean, Japanese, and Chinese. Usage with other languages may result in degraded performance.
|
| 207 |
+
- Knowledge Cutoff: The model's information is limited to data available up to August 2023.
|
| 208 |
+
- Safety Mechanisms: This release does not yet include comprehensive safety features. Future updates will address this area.
|
| 209 |
+
- Release Status: This is a preliminary release version with planned enhancements and updates forthcoming.
|
| 210 |
+
|
| 211 |
+
|
| 212 |
+
## License
|
| 213 |
+
This model repository is licensed under the Apache-2.0 License.
|
| 214 |
+
|
| 215 |
+
|
| 216 |
+
## Citation
|
| 217 |
+
```
|
| 218 |
+
@article{trillion7bpreview,
|
| 219 |
+
title={Trillion-7b-preview},
|
| 220 |
+
author={trillionlabs},
|
| 221 |
+
year={2025},
|
| 222 |
+
url={https://huggingface.co/trillionlabs/trillion-7b-preview-test}
|
| 223 |
+
}
|
| 224 |
+
```
|
| 225 |
+
|
| 226 |
+
## Contact
|
| 227 |
+
For inquiries, please contact: info@trillionlabs.co
|
assets/Signiture_Trillion_BlackBG.png
ADDED
|
Git LFS Details
|
assets/Signiture_Trillion_WhiteBG.png
ADDED
|
Git LFS Details
|
assets/frontier.png
ADDED
|
config.json
ADDED
|
@@ -0,0 +1,29 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"LlamaForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_bias": false,
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"bos_token_id": 0,
|
| 8 |
+
"eos_token_id": 128001,
|
| 9 |
+
"head_dim": 128,
|
| 10 |
+
"hidden_act": "silu",
|
| 11 |
+
"hidden_size": 4096,
|
| 12 |
+
"initializer_range": 0.02,
|
| 13 |
+
"intermediate_size": 11008,
|
| 14 |
+
"max_position_embeddings": 4096,
|
| 15 |
+
"mlp_bias": false,
|
| 16 |
+
"model_type": "llama",
|
| 17 |
+
"num_attention_heads": 32,
|
| 18 |
+
"num_hidden_layers": 32,
|
| 19 |
+
"num_key_value_heads": 32,
|
| 20 |
+
"pretraining_tp": 1,
|
| 21 |
+
"rms_norm_eps": 1e-05,
|
| 22 |
+
"rope_scaling": null,
|
| 23 |
+
"rope_theta": 100000.0,
|
| 24 |
+
"tie_word_embeddings": false,
|
| 25 |
+
"torch_dtype": "bfloat16",
|
| 26 |
+
"transformers_version": "4.49.0.dev0",
|
| 27 |
+
"use_cache": true,
|
| 28 |
+
"vocab_size": 128128
|
| 29 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
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"model.layers.8.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
|
| 283 |
+
"model.layers.8.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
| 284 |
+
"model.layers.8.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
| 285 |
+
"model.layers.8.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
| 286 |
+
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
| 287 |
+
"model.layers.9.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
| 288 |
+
"model.layers.9.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
| 289 |
+
"model.layers.9.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
|
| 290 |
+
"model.layers.9.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
| 291 |
+
"model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
| 292 |
+
"model.layers.9.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
| 293 |
+
"model.layers.9.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
| 294 |
+
"model.layers.9.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
| 295 |
+
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
| 296 |
+
"model.norm.weight": "model-00003-of-00004.safetensors"
|
| 297 |
+
}
|
| 298 |
+
}
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,153 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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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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|
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|
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|
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|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"additional_special_tokens": [
|
| 3 |
+
"<|reserved_token_1|>",
|
| 4 |
+
"<|reserved_token_2|>",
|
| 5 |
+
"<|reserved_token_3|>",
|
| 6 |
+
"<|reserved_token_4|>",
|
| 7 |
+
"<|reserved_token_5|>",
|
| 8 |
+
"<|reserved_token_6|>",
|
| 9 |
+
"<|reserved_token_7|>",
|
| 10 |
+
"<|reserved_token_8|>",
|
| 11 |
+
"<|reserved_token_9|>",
|
| 12 |
+
"<|reserved_token_10|>",
|
| 13 |
+
"<|reserved_token_11|>",
|
| 14 |
+
"<|reserved_token_12|>",
|
| 15 |
+
"<|reserved_token_13|>",
|
| 16 |
+
"<|reserved_token_14|>",
|
| 17 |
+
"<|reserved_token_15|>",
|
| 18 |
+
"<|reserved_token_16|>",
|
| 19 |
+
"<|reserved_token_17|>",
|
| 20 |
+
"<|reserved_token_18|>",
|
| 21 |
+
"<|reserved_token_19|>",
|
| 22 |
+
"<|reserved_token_20|>",
|
| 23 |
+
"<|reserved_token_21|>",
|
| 24 |
+
"<|reserved_token_22|>",
|
| 25 |
+
"<|reserved_token_23|>",
|
| 26 |
+
"<|reserved_token_24|>",
|
| 27 |
+
"<|reserved_token_25|>",
|
| 28 |
+
"<|reserved_token_26|>",
|
| 29 |
+
"<|reserved_token_27|>",
|
| 30 |
+
"<|reserved_token_28|>",
|
| 31 |
+
"<|reserved_token_29|>",
|
| 32 |
+
"<|reserved_token_30|>",
|
| 33 |
+
"<|reserved_token_31|>",
|
| 34 |
+
"<|reserved_token_32|>",
|
| 35 |
+
"<|reserved_token_33|>",
|
| 36 |
+
"<|reserved_token_34|>",
|
| 37 |
+
"<|reserved_token_35|>",
|
| 38 |
+
"<|reserved_token_36|>",
|
| 39 |
+
"<|reserved_token_37|>",
|
| 40 |
+
"<|reserved_token_38|>",
|
| 41 |
+
"<|reserved_token_39|>",
|
| 42 |
+
"<|reserved_token_40|>",
|
| 43 |
+
"<|reserved_token_41|>",
|
| 44 |
+
"<|reserved_token_42|>",
|
| 45 |
+
"<|reserved_token_43|>",
|
| 46 |
+
"<|reserved_token_44|>",
|
| 47 |
+
"<|reserved_token_45|>",
|
| 48 |
+
"<|reserved_token_46|>",
|
| 49 |
+
"<|reserved_token_47|>",
|
| 50 |
+
"<|reserved_token_48|>",
|
| 51 |
+
"<|reserved_token_49|>",
|
| 52 |
+
"<|reserved_token_50|>",
|
| 53 |
+
"<|reserved_token_51|>",
|
| 54 |
+
"<|reserved_token_52|>",
|
| 55 |
+
"<|reserved_token_53|>",
|
| 56 |
+
"<|reserved_token_54|>",
|
| 57 |
+
"<|reserved_token_55|>",
|
| 58 |
+
"<|reserved_token_56|>",
|
| 59 |
+
"<|reserved_token_57|>",
|
| 60 |
+
"<|reserved_token_58|>",
|
| 61 |
+
"<|reserved_token_59|>",
|
| 62 |
+
"<|reserved_token_60|>",
|
| 63 |
+
"<|reserved_token_61|>",
|
| 64 |
+
"<|reserved_token_62|>",
|
| 65 |
+
"<|reserved_token_63|>",
|
| 66 |
+
"<|reserved_token_64|>",
|
| 67 |
+
"<|reserved_token_65|>",
|
| 68 |
+
"<|reserved_token_66|>",
|
| 69 |
+
"<|reserved_token_67|>",
|
| 70 |
+
"<|reserved_token_68|>",
|
| 71 |
+
"<|reserved_token_69|>",
|
| 72 |
+
"<|reserved_token_70|>",
|
| 73 |
+
"<|reserved_token_71|>",
|
| 74 |
+
"<|reserved_token_72|>",
|
| 75 |
+
"<|reserved_token_73|>",
|
| 76 |
+
"<|reserved_token_74|>",
|
| 77 |
+
"<|reserved_token_75|>",
|
| 78 |
+
"<|reserved_token_76|>",
|
| 79 |
+
"<|reserved_token_77|>",
|
| 80 |
+
"<|reserved_token_78|>",
|
| 81 |
+
"<|reserved_token_79|>",
|
| 82 |
+
"<|reserved_token_80|>",
|
| 83 |
+
"<|reserved_token_81|>",
|
| 84 |
+
"<|reserved_token_82|>",
|
| 85 |
+
"<|reserved_token_83|>",
|
| 86 |
+
"<|reserved_token_84|>",
|
| 87 |
+
"<|reserved_token_85|>",
|
| 88 |
+
"<|reserved_token_86|>",
|
| 89 |
+
"<|reserved_token_87|>",
|
| 90 |
+
"<|reserved_token_88|>",
|
| 91 |
+
"<|reserved_token_89|>",
|
| 92 |
+
"<|reserved_token_90|>",
|
| 93 |
+
"<|reserved_token_91|>",
|
| 94 |
+
"<|reserved_token_92|>",
|
| 95 |
+
"<|reserved_token_93|>",
|
| 96 |
+
"<|reserved_token_94|>",
|
| 97 |
+
"<|reserved_token_95|>",
|
| 98 |
+
"<|reserved_token_96|>",
|
| 99 |
+
"<|reserved_token_97|>",
|
| 100 |
+
"<|reserved_token_98|>",
|
| 101 |
+
"<|reserved_token_99|>",
|
| 102 |
+
"<|reserved_token_100|>",
|
| 103 |
+
"<|reserved_token_101|>",
|
| 104 |
+
"<|reserved_token_102|>",
|
| 105 |
+
"<|reserved_token_103|>",
|
| 106 |
+
"<|reserved_token_104|>",
|
| 107 |
+
"<|reserved_token_105|>",
|
| 108 |
+
"<|reserved_token_106|>",
|
| 109 |
+
"<|reserved_token_107|>",
|
| 110 |
+
"<|reserved_token_108|>",
|
| 111 |
+
"<|reserved_token_109|>",
|
| 112 |
+
"<|reserved_token_110|>",
|
| 113 |
+
"<|reserved_token_111|>",
|
| 114 |
+
"<|reserved_token_112|>",
|
| 115 |
+
"<|reserved_token_113|>",
|
| 116 |
+
"<|reserved_token_114|>",
|
| 117 |
+
"<|reserved_token_115|>",
|
| 118 |
+
"<|reserved_token_116|>",
|
| 119 |
+
"<|reserved_token_117|>",
|
| 120 |
+
"<|reserved_token_118|>",
|
| 121 |
+
"<|reserved_token_119|>",
|
| 122 |
+
"<|reserved_token_120|>",
|
| 123 |
+
"<|reserved_token_121|>"
|
| 124 |
+
],
|
| 125 |
+
"bos_token": {
|
| 126 |
+
"content": "<|endoftext|>",
|
| 127 |
+
"lstrip": false,
|
| 128 |
+
"normalized": false,
|
| 129 |
+
"rstrip": false,
|
| 130 |
+
"single_word": false
|
| 131 |
+
},
|
| 132 |
+
"eos_token": {
|
| 133 |
+
"content": "<|im_end|>",
|
| 134 |
+
"lstrip": false,
|
| 135 |
+
"normalized": false,
|
| 136 |
+
"rstrip": false,
|
| 137 |
+
"single_word": false
|
| 138 |
+
},
|
| 139 |
+
"pad_token": {
|
| 140 |
+
"content": "<|pad|>",
|
| 141 |
+
"lstrip": false,
|
| 142 |
+
"normalized": false,
|
| 143 |
+
"rstrip": false,
|
| 144 |
+
"single_word": false
|
| 145 |
+
},
|
| 146 |
+
"unk_token": {
|
| 147 |
+
"content": "<|endoftext|>",
|
| 148 |
+
"lstrip": false,
|
| 149 |
+
"normalized": false,
|
| 150 |
+
"rstrip": false,
|
| 151 |
+
"single_word": false
|
| 152 |
+
}
|
| 153 |
+
}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,1169 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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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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|
|
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|
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|
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| 1 |
+
{
|
| 2 |
+
"added_tokens_decoder": {
|
| 3 |
+
"0": {
|
| 4 |
+
"content": "<|endoftext|>",
|
| 5 |
+
"lstrip": false,
|
| 6 |
+
"normalized": false,
|
| 7 |
+
"rstrip": false,
|
| 8 |
+
"single_word": false,
|
| 9 |
+
"special": true
|
| 10 |
+
},
|
| 11 |
+
"128000": {
|
| 12 |
+
"content": "<|im_start|>",
|
| 13 |
+
"lstrip": false,
|
| 14 |
+
"normalized": false,
|
| 15 |
+
"rstrip": false,
|
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|
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|
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|
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|
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|
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|
| 885 |
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|
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|
| 888 |
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|
| 889 |
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|
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|
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| 1079 |
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| 1080 |
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| 1082 |
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| 1122 |
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| 1123 |
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"<|reserved_token_87|>",
|
| 1124 |
+
"<|reserved_token_88|>",
|
| 1125 |
+
"<|reserved_token_89|>",
|
| 1126 |
+
"<|reserved_token_90|>",
|
| 1127 |
+
"<|reserved_token_91|>",
|
| 1128 |
+
"<|reserved_token_92|>",
|
| 1129 |
+
"<|reserved_token_93|>",
|
| 1130 |
+
"<|reserved_token_94|>",
|
| 1131 |
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"<|reserved_token_95|>",
|
| 1132 |
+
"<|reserved_token_96|>",
|
| 1133 |
+
"<|reserved_token_97|>",
|
| 1134 |
+
"<|reserved_token_98|>",
|
| 1135 |
+
"<|reserved_token_99|>",
|
| 1136 |
+
"<|reserved_token_100|>",
|
| 1137 |
+
"<|reserved_token_101|>",
|
| 1138 |
+
"<|reserved_token_102|>",
|
| 1139 |
+
"<|reserved_token_103|>",
|
| 1140 |
+
"<|reserved_token_104|>",
|
| 1141 |
+
"<|reserved_token_105|>",
|
| 1142 |
+
"<|reserved_token_106|>",
|
| 1143 |
+
"<|reserved_token_107|>",
|
| 1144 |
+
"<|reserved_token_108|>",
|
| 1145 |
+
"<|reserved_token_109|>",
|
| 1146 |
+
"<|reserved_token_110|>",
|
| 1147 |
+
"<|reserved_token_111|>",
|
| 1148 |
+
"<|reserved_token_112|>",
|
| 1149 |
+
"<|reserved_token_113|>",
|
| 1150 |
+
"<|reserved_token_114|>",
|
| 1151 |
+
"<|reserved_token_115|>",
|
| 1152 |
+
"<|reserved_token_116|>",
|
| 1153 |
+
"<|reserved_token_117|>",
|
| 1154 |
+
"<|reserved_token_118|>",
|
| 1155 |
+
"<|reserved_token_119|>",
|
| 1156 |
+
"<|reserved_token_120|>",
|
| 1157 |
+
"<|reserved_token_121|>"
|
| 1158 |
+
],
|
| 1159 |
+
"bos_token": "<|endoftext|>",
|
| 1160 |
+
"chat_template": "{{- bos_token }}{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
|
| 1161 |
+
"clean_up_tokenization_spaces": false,
|
| 1162 |
+
"eos_token": "<|im_end|>",
|
| 1163 |
+
"extra_special_tokens": {},
|
| 1164 |
+
"model_max_length": 4096,
|
| 1165 |
+
"pad_token": "<|pad|>",
|
| 1166 |
+
"padding_side": "left",
|
| 1167 |
+
"tokenizer_class": "PreTrainedTokenizer",
|
| 1168 |
+
"unk_token": "<|endoftext|>"
|
| 1169 |
+
}
|