初始化项目，由ModelHub XC社区提供模型

Model: stepfun-ai/StepFun-Prover-Preview-7B
Source: Original Platform

.gitattributes

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LICENSE

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README.md

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+---
+language:
+- en
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
+tags:
+- chat
+library_name: transformers
+license: apache-2.0
+---
+
+# StepFun-Prover-Preview-7B
+
+**StepFun-Prover-Preview-7B** is a theorem proving model developed by StepFun Team. It can iteratively refine the proof sketch via interacting with Lean4, and achieve 66.0% accuracy with Pass@1 on MiniF2F-test. Advanced usage examples can be seen in [github](https://github.com/stepfun-ai/StepFun-Prover-Preview).
+
+# Quick Start with vLLM
+
+```python
+from vllm import LLM, SamplingParams
+from transformers import AutoTokenizer
+
+model_name = "Stepfun/Stepfun-Prover-Preview-7B"
+model = LLM(
+    model=model_name,
+    tensor_parallel_size=4,
+    )
+tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
+
+formal_problem = """
+import Mathlib
+
+theorem test_theorem (x y z : ℝ) (hx : 0 < x) (hy : 0 < y) (hz : 0 < z) :
+    (x^2 - z^2) / (y + z) + (y^2 - x^2) / (z + x) + (z^2 - y^2) / (x + y) ≥ 0 := by
+""".strip()
+
+system_prompt = "You will be given an unsolved Lean 4 problem. Think carefully and work towards a solution. At any point, you may use the Lean 4 REPL to check your progress by enclosing your partial solution between <sketch> and </sketch>. The REPL feedback will be provided between <REPL> and </REPL>. Continue this process as needed until you arrive at a complete and correct solution."
+
+user_prompt = f"```lean4\n{formal_problem}\n```"
+
+dialog = [
+  {"role": "system", "content": system_prompt},
+  {"role": "user", "content": user_prompt}
+] 
+
+prompt = tokenizer.apply_chat_template(dialog, tokenize=False, add_generation_prompt=True)
+
+sampling_params = SamplingParams(
+    temperature=0.999,
+    top_p=0.95,
+    top_k=-1,
+    max_tokens=16384,
+    stop_token_ids=[151643, 151666], # <｜end▁of▁sentence｜>, </sketch>
+    include_stop_str_in_output=True,
+)
+
+output = model.generate(prompt, sampling_params=sampling_params)
+output_text = output[0].outputs[0].text
+print(output_text)
+```

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='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- 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 %}{{'\n<｜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_tool %}{{'<｜Assistant｜><think>\n'}}{% endif %}

config.json

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+{
+    "architectures": [
+        "Qwen2ForCausalLM"
+    ],
+    "attention_dropout": 0.0,
+    "bos_token_id": 151643,
+    "eos_token_id": 151643,
+    "hidden_act": "silu",
+    "hidden_size": 3584,
+    "initializer_range": 0.02,
+    "intermediate_size": 18944,
+    "max_position_embeddings": 131072,
+    "max_window_layers": 28,
+    "model_type": "qwen2",
+    "num_attention_heads": 28,
+    "num_hidden_layers": 28,
+    "num_key_value_heads": 4,
+    "rms_norm_eps": 1e-06,
+    "rope_theta": 10000,
+    "sliding_window": 4096,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.44.0",
+    "use_cache": true,
+    "use_mrope": false,
+    "use_sliding_window": false,
+    "vocab_size": 152064
+}

configuration.json

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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

generate_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 151646,
+  "eos_token_id": 151643,
+  "do_sample": true,
+  "temperature": 0.7,
+  "top_p": 0.95,
+  "transformers_version": "4.54.0"
+}

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special_tokens_map.json

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tokenizer.json

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tokenizer_config.json

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