初始化项目，由ModelHub XC社区提供模型

Model: Amu/t1-1.5B
Source: Original Platform

README.md

@@ -0,0 +1,82 @@
+---
+license: mit
+language:
+- am
+- ar
+- bn
+- zh
+- cs
+- nl
+- en
+- fr
+- de
+- el
+- ha
+- he
+- hi
+- id
+- it
+- ja
+- jv
+- km
+- ko
+- lo
+- ms
+- mr
+- fa
+- pl
+- pt
+- ro
+- ru
+- es
+- sw
+- sv
+- tl
+- ta
+- te
+- th
+- tr
+- uk
+- ur
+- vi
+datasets:
+- simplescaling/s1K
+- lightblue/reasoning-multilingual-R1-Llama-70B-train
+base_model:
+- Qwen/Qwen2.5-1.5B-Instruct
+library_name: transformers
+---
+It's a 1.5B model.
+
+It's a distill model like s1 and deepseek-r1-distill.
+
+It's test model. I hope I can reproduce a rl model like RL-Zero.
+
+This model is a mini-step.
+
+Thanks for evveryone in the open community.
+
+how to use:
+```
+from vllm import LLM, SamplingParams
+from transformers import AutoTokenizer
+
+model = LLM(
+    "Amu/t1-1.5B"
+)
+tok = AutoTokenizer.from_pretrained("simplescaling/s1-32B")
+
+stop_token_ids = tok("<|im_end|>")["input_ids"]
+
+sampling_params = SamplingParams(
+    max_tokens=32768,
+    min_tokens=0,
+    stop_token_ids=stop_token_ids,
+)
+
+prompt = "How many r in raspberry"
+prompt = "<|im_start|>system\nYou are t1, created by Amu. You are a helpful assistant.<|im_end|>\n<|im_start|>user\n" + prompt + "<|im_end|>\n<|im_start|>assistant\n"
+
+o = model.generate(prompt, sampling_params=sampling_params)
+print(o[0].outputs[0].text)
+```