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Model: RickyDeSkywalker/GAR_DeepSeek-Prover-V2 Source: Original Platform
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README.md
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---
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base_model:
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- deepseek-ai/DeepSeek-Prover-V2-7B
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license: mit
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- math
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- lean
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- theorem-proving
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- reinforcement-learning
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---
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# GAR: Generative Adversarial Reinforcement Learning for Formal Theorem Proving
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This is the official model for **GAR: Generative Adversarial Reinforcement Learning**, a framework that jointly trains a problem composer and solver in an adversarial loop for formal theorem proving.
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- **Paper:** [GAR: Generative Adversarial Reinforcement Learning for Formal Theorem Proving](https://huggingface.co/papers/2510.11769)
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- **Repository:** [GAR-Official](https://github.com/RickySkywalker/GAR-Official)
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- **Authors:** Ruida Wang, Jiarui Yao, [Rui Pan](https://huggingface.co/research4pan), Shizhe Diao, Tong Zhang
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## Introduction
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We introduce **GAR: Generative Adversarial Reinforcement Learning**, an RL training method that intends to solve inefficiency and suboptimial performance in formal theorem prover training caused by fixed problem sets. GAR jointly trains the problem composer and solver in an adversarial loop, which introduces an implicit curriculum learning mechanism, aligning the task difficulty with the prover's evolving capability to improve training efficiency and enabling stronger model performance.
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Experiments indicates that GAR trained models (such as Goedel-Prover-V2-8B and DeepSeek-Prover-V2-7B) achieve an average of 4.20% of enhancement on MiniF2F-Test under pass@32, and improve the DeepSeek-Prover-V2's pass@32 performance on ProofNet-Test from 22.58% to 25.81%.
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## Related Artifacts
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### Trained Models
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* **GAR_Goedel-Prover-V2:** [RickyDeSkywalker/GAR_Goedel-Prover-V2](https://huggingface.co/RickyDeSkywalker/GAR_Goedel-Prover-V2)
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* **GAR_DeepSeek-Prover-V2 (this repo):** [RickyDeSkywalker/GAR_DeepSeek-Prover-V2](https://huggingface.co/RickyDeSkywalker/GAR_DeepSeek-Prover-V2/)
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### Base Datasets
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* **Original base dataset:** [RickyDeSkywalker/GAR_baseDataset](https://huggingface.co/datasets/RickyDeSkywalker/GAR_baseDataset)
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* **Base dataset under Numina-Math:** [RickyDeSkywalker/GAR_baseDataset_NuminaMath](https://huggingface.co/datasets/RickyDeSkywalker/GAR_baseDataset_NuminaMath)
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## Training Guide
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### Clone repository
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Clone the repo using the following command:
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```bash
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git clone --recurse-submodules git@github.com:RickySkywalker/GAR-Official.git
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```
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### Init Lean server
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We apply KiminaLeanServer as the Lean verification server. It can be initialized by:
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```bash
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cd KiminaLeanServer
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cp .env.template .env
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docker compose up -d
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```
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### Setup environment
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The environment can be set up by running the following command:
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```bash
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conda env create -f environment.yaml
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```
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### Clone base dataset
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Clone and transform the dataset into JSON form:
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```python
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from datasets import load_dataset
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ds = load_dataset("RickyDeSkywalker/GAR_baseDataset_NuminaMath")
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ds["train"].to_json("./base_data/GAR_base_data_Numina-Math.json")
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```
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### Run training
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The GAR training can be initialized through the following command, detailed training config can be found in `./main.py`.
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```bash
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python -u ./main.py \
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--training_name GAR-Prover \
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--base_data_path ./base_data/GAR_base_data_Numina-Math.json
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```
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## Citation
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```bibtex
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@article{wang2025gar,
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title={GAR: Generative Adversarial Reinforcement Learning for Formal Theorem Proving},
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author={Wang, Ruida and Yao, Jiarui and Pan, Rui and Diao, Shizhe and Zhang, Tong},
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journal={arXiv preprint arXiv:2510.11769},
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year={2025}
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}
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```
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## Acknowledgement
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This material is based upon work supported partially by NSF under Grant No. 2416897, Grant No. 2505932, and by ORN under Grant No. N000142512318. This research used both Delta (NSF award OAC 2005572) and DeltaAI (NSF award OAC 2320345) advanced computing systems, and computing resources provided by NAIRR Pilot NAIRR250157.
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chat_template.jinja
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{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='', is_first_sp=true, is_last_user=false) %}{%- for message in messages %}{%- if message['role'] == 'system' %}{%- if ns.is_first_sp %}{% set ns.system_prompt = ns.system_prompt + message['content'] %}{% set ns.is_first_sp = false %}{%- else %}{% set ns.system_prompt = ns.system_prompt + '
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' + message['content'] %}{%- endif %}{%- endif %}{%- endfor %}{{ bos_token }}{{ ns.system_prompt }}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{%- set ns.is_first = false -%}{%- set ns.is_last_user = true -%}{{'<｜User｜>' + message['content'] + '<｜Assistant｜>'}}{%- endif %}{%- if message['role'] == 'assistant' and message['tool_calls'] is defined and message['tool_calls'] is not none %}{%- set ns.is_last_user = false -%}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{%- endif %}{%- set ns.is_first = false %}{%- set ns.is_tool = false -%}{%- set ns.is_output_first = true %}{%- for tool in message['tool_calls'] %}{%- if not ns.is_first %}{%- if message['content'] is none %}{{'<｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '
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' + '```json' + '
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' + tool['function']['arguments'] + '
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' + '```' + '<｜tool▁call▁end｜>'}}{%- else %}{{message['content'] + '<｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '
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' + '```json' + '
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' + tool['function']['arguments'] + '
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' + '```' + '<｜tool▁call▁end｜>'}}{%- endif %}{%- set ns.is_first = true -%}{%- else %}{{'
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' + '```' + '<｜tool▁call▁end｜>'}}{%- endif %}{%- endfor %}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- if message['role'] == 'assistant' and (message['tool_calls'] is not defined or message['tool_calls'] is none)%}{%- set ns.is_last_user = false -%}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{{content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_last_user = false -%}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'
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<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_last_user and not ns.is_tool %}{{'<｜Assistant｜>'}}{% endif %}
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config.json
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"architectures": [
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"LlamaForCausalLM"
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 100000,
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"eos_token_id": 100001,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-06,
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"rope_scaling": {
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"beta_fast": 32,
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"factor": 16,
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"mscale": true,
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"rope_type": "yarn",
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"type": "yarn"
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"rope_theta": 10000,
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"tie_word_embeddings": false,
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"use_cache": false,
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"vocab_size": 102400
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"model.layers.7.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.norm.weight": "model-00004-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<｜begin▁of▁sentence｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<｜end▁of▁sentence｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<｜end▁of▁sentence｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
499362
tokenizer.json
Normal file
499362
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
166
tokenizer_config.json
Normal file
166
tokenizer_config.json
Normal file
@@ -0,0 +1,166 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": true,
|
||||
"add_prefix_space": null,
|
||||
"added_tokens_decoder": {
|
||||
"100000": {
|
||||
"content": "<｜begin▁of▁sentence｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100001": {
|
||||
"content": "<｜end▁of▁sentence｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100002": {
|
||||
"content": "<｜fim▁hole｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"100003": {
|
||||
"content": "<｜fim▁begin｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"100004": {
|
||||
"content": "<｜fim▁end｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"100005": {
|
||||
"content": "<｜completion｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"100006": {
|
||||
"content": "<｜User｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"100007": {
|
||||
"content": "<｜Assistant｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"100008": {
|
||||
"content": "<|EOT|>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100009": {
|
||||
"content": "<｜tool▁calls▁begin｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"100010": {
|
||||
"content": "<｜tool▁calls▁end｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"100011": {
|
||||
"content": "<｜tool▁call▁begin｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"100012": {
|
||||
"content": "<｜tool▁call▁end｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"100013": {
|
||||
"content": "<｜tool▁outputs▁begin｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"100014": {
|
||||
"content": "<｜tool▁outputs▁end｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"100015": {
|
||||
"content": "<｜tool▁output▁begin｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"100016": {
|
||||
"content": "<｜tool▁output▁end｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"100017": {
|
||||
"content": "<｜tool▁sep｜>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"bos_token": "<｜begin▁of▁sentence｜>",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<｜end▁of▁sentence｜>",
|
||||
"extra_special_tokens": {},
|
||||
"legacy": true,
|
||||
"max_length": 4096,
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<｜end▁of▁sentence｜>",
|
||||
"sp_model_kwargs": {},
|
||||
"stride": 0,
|
||||
"tokenizer_class": "LlamaTokenizerFast",
|
||||
"truncation_side": "right",
|
||||
"truncation_strategy": "longest_first",
|
||||
"unk_token": null,
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user