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update the supported models
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‎README.md‎

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@@ -112,35 +112,31 @@ supported on Twinkle✨ framework.
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> both Tinker APIs, as well as the full-fledged Twinkle✨ native APIs. The serverless endpoint is backed
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> by one training base at a time, and currently it is [Qwen3-30B-A3B-Instruct-2507](https://modelscope.cn/models/Qwen/Qwen3-30B-A3B-Instruct-2507).
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| Model Type | Model ID on [ModelScope](https://modelscope.cn) | Requires | Megatron Support | HF Model ID |
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| ------------------- |--------------------------------------------------------------------------------------------------------------------------| -------------------- | ---------------- | ---------------------------------------------------------------------------------------------------------- |
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| qwen3 series | [Qwen/Qwen3-0.6B-Base](https://modelscope.cn/models/Qwen/Qwen3-0.6B-Base)~32B | transformers>=4.51 | ✅ | [Qwen/Qwen3-0.6B-Base](https://huggingface.co/Qwen/Qwen3-0.6B-Base) |
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| qwen3_moe series | [Qwen/Qwen3-30B-A3B-Base](https://modelscope.cn/models/Qwen/Qwen3-30B-A3B-Base) | transformers>=4.51 | ✅ | [Qwen/Qwen3-30B-A3B-Base](https://huggingface.co/Qwen/Qwen3-30B-A3B-Base) |
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| | [Qwen/Qwen3-30B-A3B](https://modelscope.cn/models/Qwen/Qwen3-30B-A3B)~235B | transformers>=4.51 | ✅ | [Qwen/Qwen3-30B-A3B](https://huggingface.co/Qwen/Qwen3-30B-A3B) |
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| qwen2 series | [Qwen/Qwen2-0.5B-Instruct](https://modelscope.cn/models/Qwen/Qwen2-0.5B-Instruct) ~72B | transformers>=4.37 | ✅ | [Qwen/Qwen2-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2-0.5B-Instruct) |
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| | [Qwen/Qwen2.5-0.5B-Instruct](https://modelscope.cn/models/Qwen/Qwen2.5-0.5B-Instruct)~72B | transformers>=4.37 | ✅ | [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) |
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| | [Qwen/Qwen2.5-0.5B](https://modelscope.cn/models/Qwen/Qwen2.5-0.5B)~72B | transformers>=4.37 | ✅ | [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) |
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| qwen2_moe series | [Qwen/Qwen1.5-MoE-A2.7B-Chat](https://modelscope.cn/models/Qwen/Qwen1.5-MoE-A2.7B-Chat) | transformers>=4.40 | ✅ | [Qwen/Qwen1.5-MoE-A2.7B-Chat](https://huggingface.co/Qwen/Qwen1.5-MoE-A2.7B-Chat) |
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| chatglm4 series | [ZhipuAI/glm-4-9b-chat](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat) | transformers>=4.42 | ✘ | [zai-org/glm-4-9b-chat](https://huggingface.co/zai-org/glm-4-9b-chat) |
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| | [ZhipuAI/LongWriter-glm4-9b](https://modelscope.cn/models/ZhipuAI/LongWriter-glm4-9b) | transformers>=4.42 | ✘ | [zai-org/LongWriter-glm4-9b](https://huggingface.co/zai-org/LongWriter-glm4-9b) |
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| glm_edge series | [ZhipuAI/glm-edge-1.5b-chat](https://modelscope.cn/models/ZhipuAI/glm-edge-1.5b-chat) | transformers>=4.46 | ✘ | [zai-org/glm-edge-1.5b-chat](https://huggingface.co/zai-org/glm-edge-1.5b-chat) |
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| | [ZhipuAI/glm-edge-4b-chat](https://modelscope.cn/models/ZhipuAI/glm-edge-4b-chat) | transformers>=4.46 | ✘ | [zai-org/glm-edge-4b-chat](https://huggingface.co/zai-org/glm-edge-4b-chat) |
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| internlm2 series | [Shanghai_AI_Laboratory/internlm2-1_8b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-1_8b) | transformers>=4.38 | ✘ | [internlm/internlm2-1_8b](https://huggingface.co/internlm/internlm2-1_8b) |
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| | [Shanghai_AI_Laboratory/internlm2-chat-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-7b) | transformers>=4.38 | ✘ | [internlm/internlm2-chat-7b](https://huggingface.co/internlm/internlm2-chat-7b) |
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| deepseek_v1 | [deepseek-ai/deepseek-vl-7b-chat](https://modelscope.cn/models/deepseek-ai/deepseek-vl-7b-chat) | transformers>=4.39.4 | ✅ | —— |
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| | [deepseek-ai/DeepSeek-V2-Lite](https://modelscope.cn/models/deepseek-ai/DeepSeek-V2-Lite) | transformers>=4.39.3 | ✅ | [deepseek-ai/DeepSeek-V2-Lite](https://huggingface.co/deepseek-ai/DeepSeek-V2-Lite) |
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| | [deepseek-ai/DeepSeek-V2.5](https://modelscope.cn/models/deepseek-ai/DeepSeek-V2.5) | transformers>=4.39.3 | ✅ | [deepseek-ai/DeepSeek-V2.5](https://huggingface.co/deepseek-ai/DeepSeek-V2.5) |
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| | [deepseek-ai/DeepSeek-R1](https://modelscope.cn/models/deepseek-ai/DeepSeek-R1) | transformers>=4.39.3 | ✅ | [deepseek-ai/DeepSeek-R1](https://huggingface.co/deepseek-ai/DeepSeek-R1) |
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| deepSeek-r1-distill | [deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B](https://modelscope.cn/models/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B) ~32B | transformers>=4.37 | ✅ | [deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B) |
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| Model Type | Model ID on [ModelScope](https://modelscope.cn) | Model Size | Requires | Support Megatron | HF Model ID |
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| ------------------- | ------------------------------------------------------------ | :-------------------------------------: | -------------------- | :--------------: | :----------------------------------------------------------: |
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| qwen3 series | [Qwen/Qwen3-14B-Base](https://modelscope.cn/models/Qwen/Qwen3-14B-Base) | 0.6B/1.7B/4B/8B/14B | transformers>=4.51 | ✔ | [Qwen/Qwen3-14B-Base](https://huggingface.co/Qwen/Qwen3-14B-Base) |
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| | [Qwen/Qwen3-32B](https://modelscope.cn/models/Qwen/Qwen3-32B) | 0.6B/1.7B/4B/8B/14B/32B | transformers>=4.51 | ✔ | [Qwen/Qwen3-32B](https://huggingface.co/Qwen/Qwen3-32B) |
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| qwen3_moe series | [Qwen/Qwen3-30B-A3B-Base](https://modelscope.cn/models/Qwen/Qwen3-30B-A3B-Base) | 30B-A3B/A3B-Base,235B-A22B | transformers>=4.51 | ✔ | [Qwen/Qwen3-30B-A3B-Base](https://huggingface.co/Qwen/Qwen3-30B-A3B-Base) |
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| qwen2 series | [Qwen/Qwen2-0.5B-Instruct](https://modelscope.cn/models/Qwen/Qwen2-0.5B-Instruct) | 0.5B/1.5B/7B/72B | transformers>=4.37 | ✔ | [Qwen/Qwen2-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2-0.5B-Instruct) |
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| | [Qwen/Qwen2-1.5B](https://modelscope.cn/models/Qwen/Qwen2-1.5B) | 0.5B/1.5B/7B/72B | transformers>=4.37 | ✔ | [Qwen/Qwen2-1.5B](https://huggingface.co/Qwen/Qwen2-1.5B) |
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| | [Qwen/Qwen2.5-1.5B-Instruct](https://modelscope.cn/models/Qwen/Qwen2.5-1.5B-Instruct) | 0.5B/1.5B/3B/7B/14B/32B/72B | transformers>=4.37 | ✔ | [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) |
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| | [Qwen/Qwen2.5-0.5B](https://modelscope.cn/models/Qwen/Qwen2.5-0.5B) | 0.5B/1.5B/3B/7B/14B/32B | transformers>=4.37 | ✔ | [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) |
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| qwen2_moe series | [Qwen/Qwen1.5-MoE-A2.7B-Chat](https://modelscope.cn/models/Qwen/Qwen1.5-MoE-A2.7B-Chat) | - | transformers>=4.40 | ✔ | [Qwen/Qwen1.5-MoE-A2.7B-Chat](https://huggingface.co/Qwen/Qwen1.5-MoE-A2.7B-Chat) |
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| | [Qwen/Qwen1.5-MoE-A2.7B](https://modelscope.cn/models/Qwen/Qwen1.5-MoE-A2.7B) | - | transformers>=4.40 | ✔ | [Qwen/Qwen1.5-MoE-A2.7B](https://huggingface.co/Qwen/Qwen1.5-MoE-A2.7B) |
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| chatglm3 series | [ZhipuAI/chatglm3-6b](https://modelscope.cn/models/ZhipuAI/chatglm3-6b) | 6b/6b-base/6b-32k/6b-128k | transformers<4.42 | ✘ | [zai-org/chatglm3-6b](https://huggingface.co/zai-org/chatglm3-6b) |
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| chatglm4 series | [ZhipuAI/glm-4-9b-chat](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat) | glm-4-9b/glm-4-9b-chat/glm-4-9b-chat-1m | transformers>=4.42 | ✘ | [zai-org/glm-4-9b-chat](https://huggingface.co/zai-org/glm-4-9b-chat) |
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| | [ZhipuAI/LongWriter-glm4-9b](https://modelscope.cn/models/ZhipuAI/LongWriter-glm4-9b) | - | transformers>=4.42 | ✘ | [zai-org/LongWriter-glm4-9b](https://huggingface.co/zai-org/LongWriter-glm4-9b) |
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| glm_edge series | [ZhipuAI/glm-edge-1.5b-chat](https://modelscope.cn/models/ZhipuAI/glm-edge-1.5b-chat) | 1.5b-chat/4b-chat | transformers>=4.46 | ✘ | [zai-org/glm-edge-1.5b-chat](https://huggingface.co/zai-org/glm-edge-1.5b-chat) |
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| internlm2 series | [Shanghai_AI_Laboratory/internlm2-1_8b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-1_8b) | 1_8b/chat-1_8b-sft/base-7b/7b/chat-7b/ | transformers>=4.38 | ✘ | [internlm/internlm2-1_8b](https://huggingface.co/internlm/internlm2-1_8b) |
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| deepseek_v1 | [deepseek-ai/DeepSeek-V2-Lite](https://modelscope.cn/models/deepseek-ai/DeepSeek-V2-Lite) | V2/V2-Lite/V2-Chat/2-Lite-Chat/V2.5 | transformers>=4.39.3 | ✔ | [deepseek-ai/DeepSeek-V2-Lite](https://huggingface.co/deepseek-ai/DeepSeek-V2-Lite) |
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| | [deepseek-ai/DeepSeek-Prover-V2-7B](https://modelscope.cn/models/deepseek-ai/DeepSeek-Prover-V2-7B) | - | transformers>=4.39.3 | ✔ | [deepseek-ai/DeepSeek-Prover-V2-7B](https://huggingface.co/deepseek-ai/DeepSeek-Prover-V2-7B) |
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| | [deepseek-ai/DeepSeek-R1](https://modelscope.cn/models/deepseek-ai/DeepSeek-R1) | - | transformers>=4.39.3 | ✔ | [deepseek-ai/DeepSeek-R1](https://huggingface.co/deepseek-ai/DeepSeek-R1) |
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| deepSeek-r1-distill | [deepseek-ai/DeepSeek-R1-Distill-Qwen-7B](https://modelscope.cn/models/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B) | 1.5B/7B/14B/32B | transformers>=4.37 | ✔ | [deepseek-ai/DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B) |
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For more detailed model support list 👉 [Quick Start](docs/source_en/Usage%20Guide/Quick-Start.md)
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## Sample Code
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Below are some of the capabilities demonstrated in the example code. For a complete introduction to training capabilities,
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please refer to [Quick Start](docs/source_en/Usage%20Guide/Quick-Start.md) and [cookbook](cookbook).
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### Train with Ray
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```python
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def train():
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# to load model from Hugging Face, use 'hf://...'
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base_model = 'ms://Qwen/Qwen3-4B'
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base_model = 'ms://Qwen/Qwen2.5-7B-Instruct'
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# 1000 samples
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dataset = Dataset(dataset_meta=DatasetMeta('ms://swift/self-cognition', data_slice=range(1000)))
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# Set template to prepare encoding
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import os
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from tqdm import tqdm
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from tinker import types
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from twinkle import init_tinker_client
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from twinkle_client import init_tinker_client
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from twinkle.dataloader import DataLoader
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from twinkle.dataset import Dataset, DatasetMeta
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from twinkle.preprocessor import SelfCognitionProcessor
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from twinkle.server.tinker.common import input_feature_to_datum
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base_model = 'ms://Qwen/Qwen3-30B-A3B-Instruct-2507'
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base_url='your-base-url'
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api_key='your-api-key'
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base_url='http://www.modelscope.cn/twinkle'
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api_key=os.environ.get('MODELSCOPE_TOKEN')
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# Use twinkle dataset to load the data
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dataset = Dataset(dataset_meta=DatasetMeta('ms://swift/self-cognition', data_slice=range(500)))
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dataset.set_template('Template', model_id=base_model, max_length=256)
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dataset.map(SelfCognitionProcessor('twinkle Model', 'ModelScope Team'), load_from_cache_file=False)
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dataset.map(SelfCognitionProcessor('twinkle Model', 'twinkle Team'), load_from_cache_file=False)
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dataset.encode(batched=True, load_from_cache_file=False)
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dataloader = DataLoader(dataset=dataset, batch_size=8)
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