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Model: sbintuitions/diafill-sarashina2.2-3b-instruct Source: Original Platform
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LICENCE
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LICENCE
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MIT License
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Copyright (c) 2025 SB Intuitions
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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README.md
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README.md
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---
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license: mit
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language:
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- ja
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pipeline_tag: text-generation
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base_model:
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- sbintuitions/sarashina2.2-3b-instruct-v0.1
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tags:
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- dialogue-generation
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- spoken-dialogue
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---
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# diafill-sarashina2.2-3b-instruct
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## Model Summary
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**DiaFill** is a Japanese dialogue script generation model designed to produce natural, spoken-style dialogue scripts rich in fillers and brief utternaces.
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Unlike typical assistant models that respond to users, this model is fine-tuned to **generate a multi-turn dialogue script between two speakers** based on a given scenario (seed data).
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## Training Data
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This model was fine-tuned on non-public Japanese dialogue script data created as part of the GENIAC (Generative AI Accelerator Challenge) project.
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The training data itself is not publicly available.
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The project is described in the following press release:
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https://www.softbank.jp/corp/news/press/sbkk/2025/20250213_01/
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## Usage (Dialogue Script Generation)
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This model generates a dialogue script based on a "Seed" prompt describing the genre, topic, and speakers.
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### Input Data Specification
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- **genre**: Choose one of the following Japanese strings:
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* `雑談` (Chit-chat)
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* `コールセンター（手続き）` (Call Center - Procedure)
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* `コールセンター（テクニカルサポート）` (Call Center - Technical Support)
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* `コールセンター（カスタマーサクセス）` (Call Center - Customer Success)
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- **industry**: Required only for Call Center genres (e.g., "家電", "通信"). **Omit this field if the genre is `雑談`.**
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- **tone**: Basically, choose either フランク (Casual) or 丁寧 (Polite) for each speaker.
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### Python Code Example
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, set_seed
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model_name = "sbintuitions/diafill-sarashina2.2-3b-instruct"
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype=torch.bfloat16,
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device_map="auto",
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)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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set_seed(42)
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seed_data = {
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"topics": ["家電保証", "修理依頼", "延長保証"],
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"genre": "コールセンター（手続き）",
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"industry": "家電",
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"speaker1_name": "田中",
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"speaker2_name": "鈴木",
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"speaker1_tone": "フランク",
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"speaker2_tone": "丁寧",
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"summary": "カスタマーは、家電保証に関する手続きについて問い合わせた。オペレーターが修理依頼や延長保証に関する詳細を案内し、カスタマーは納得して対応を依頼した。",
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}
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messages = [
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{"role": "user", "seed": seed_data},
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]
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inputs = tokenizer.apply_chat_template(
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messages,
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tokenize=True,
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add_generation_prompt=True,
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return_tensors="pt",
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).to(model.device)
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with torch.no_grad():
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outputs = model.generate(
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inputs,
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max_new_tokens=512,
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do_sample=True,
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repetition_penalty=1.1,
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)
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generated_script = tokenizer.decode(
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outputs[0][inputs.shape[1] :],
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skip_special_tokens=True,
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)
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print(generated_script)
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```
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### Generation example
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```
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カスタマー: あもしもし
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オペレーター: はい。お電話ありがとうございます。Aモバイル担当の田中でございます。本日はいかがなさいましたか？
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カスタマー: はい。えっとーちょっと家電のあのー保証について問い合わせたいんですけれども
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オペレーター: かしこまりました。保証でございますね。具体的にはどのような内容でしょうか？
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カスタマー: えーっとですね。ま保障は1年
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オペレーター: あはい。
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カスタマー: 保証されてると思うんですけども、これ例えば壊れたときとかに、どういう手続きしたらいいかっていうのを教えていただきたいです。
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オペレーター: かしこまりました。では保証の延長、また故障時の対応についてお知りになられたいとのことですね。かしこまりました。お使いいただいてる端末はAndroidとiPhoneどちらとなりますか。
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カスタマー: iPhoneです。
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オペレーター: iPhoneでございますね。かしこまりました。では詳しいご案内のために資料を確認して参りますので一旦保留といたします。お切りにならずにお待ちください。
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カスタマー: あはい。お願いします。
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```
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## License
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MIT License
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chat_template.jinja
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chat_template.jinja
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{% for message in messages %}
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{% set speaker1_label = '話者1' %}
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{% set speaker2_label = '話者2' %}
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{% if message.get('seed') and message['seed'].get('genre') and 'コールセンター' in message['seed']['genre'] %}
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{% set speaker1_label = 'オペレーター' %}{% set speaker2_label = 'カスタマー' %}
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{% endif %}
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{% if message['role'] == 'user' %}
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<|user|>以下の情報に基づいて、日本語の会話文をフィラーなども含めながら、音声での会話として自然な感じで生成してください。
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【トピック】
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{{ message['seed']['topics'] | join(', ') }}
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【会話ジャンル】
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{{ message['seed']['genre'] }}
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{% if message['seed'].get('industry') -%}
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【業界カテゴリ】
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{{ message['seed']['industry'] }}
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{% endif -%}
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【話者情報】
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{{ speaker1_label }}の名前: {{ message['seed']['speaker1_name'] }}
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{{ speaker2_label }}の名前: {{ message['seed']['speaker2_name'] }}
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{{ speaker1_label }}の話し方: {{ message['seed']['speaker1_tone'] }}
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{{ speaker2_label }}の話し方: {{ message['seed']['speaker2_tone'] }}
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【会話要約】
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{{ message['seed']['summary'] if message['seed'].get('summary') else '' }}
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</s><|assistant|>
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{% elif message['role'] == 'assistant' %}
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{{ message['content'] }}</s>
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{% endif %}
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{% endfor %}
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config.json
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config.json
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{
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"head_dim": 160,
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"hidden_act": "silu",
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"hidden_size": 2560,
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"initializer_range": 0.02,
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"intermediate_size": 8960,
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"max_position_embeddings": 8192,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 16,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 500000,
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.53.0",
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"use_cache": false,
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"vocab_size": 102400
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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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||||
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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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|
||||
"model.norm.weight": "pytorch_model-00003-of-00003.bin"
|
||||
}
|
||||
}
|
||||
51
special_tokens_map.json
Normal file
51
special_tokens_map.json
Normal file
@@ -0,0 +1,51 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"cls_token": {
|
||||
"content": "<cls>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
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|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
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|
||||
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|
||||
"single_word": false
|
||||
},
|
||||
"mask_token": {
|
||||
"content": "<mask>",
|
||||
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|
||||
"normalized": false,
|
||||
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|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
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|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"sep_token": {
|
||||
"content": "<sep>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
409855
tokenizer.json
Normal file
409855
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
3
tokenizer.model
Normal file
3
tokenizer.model
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:008293028e1a9d9a1038d9b63d989a2319797dfeaa03f171093a57b33a3a8277
|
||||
size 1831879
|
||||
171
tokenizer_config.json
Normal file
171
tokenizer_config.json
Normal file
@@ -0,0 +1,171 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_dummy_prefix_space": false,
|
||||
"add_eos_token": true,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"3": {
|
||||
"content": "<pad>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"4": {
|
||||
"content": "<sep>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"5": {
|
||||
"content": "<mask>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"6": {
|
||||
"content": "<cls>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"7": {
|
||||
"content": "<|system|>",
|
||||
"lstrip": false,
|
||||
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|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"8": {
|
||||
"content": "<|assistant|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"9": {
|
||||
"content": "<|user|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"10": {
|
||||
"content": "<|available_tools|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"11": {
|
||||
"content": "<|tool_calls|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"12": {
|
||||
"content": "<|tool_results|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"13": {
|
||||
"content": "<|code|>",
|
||||
"lstrip": false,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"14": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"102397": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"102398": {
|
||||
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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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|
||||
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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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|
||||
"extra_special_tokens": {},
|
||||
"keep_accents": true,
|
||||
"legacy": false,
|
||||
"mask_token": "<mask>",
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": "<pad>",
|
||||
"padding_side": "left",
|
||||
"sep_token": "<sep>",
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user