Instructions to use jerrycheng233/model4_dapo_16bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jerrycheng233/model4_dapo_16bit with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="jerrycheng233/model4_dapo_16bit")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("jerrycheng233/model4_dapo_16bit")
model = AutoModelForMultimodalLM.from_pretrained("jerrycheng233/model4_dapo_16bit")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jerrycheng233/model4_dapo_16bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jerrycheng233/model4_dapo_16bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jerrycheng233/model4_dapo_16bit",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/jerrycheng233/model4_dapo_16bit

SGLang

How to use jerrycheng233/model4_dapo_16bit with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "jerrycheng233/model4_dapo_16bit" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jerrycheng233/model4_dapo_16bit",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "jerrycheng233/model4_dapo_16bit" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jerrycheng233/model4_dapo_16bit",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use jerrycheng233/model4_dapo_16bit with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for jerrycheng233/model4_dapo_16bit to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for jerrycheng233/model4_dapo_16bit to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for jerrycheng233/model4_dapo_16bit to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="jerrycheng233/model4_dapo_16bit",
    max_seq_length=2048,
)

Docker Model Runner
How to use jerrycheng233/model4_dapo_16bit with Docker Model Runner:
```
docker model run hf.co/jerrycheng233/model4_dapo_16bit
```

model4_dapo_16bit / tokenizer_config.json

jerrycheng233

(Trained with Unsloth)

da3f5d2 verified 3 months ago

raw

history blame contribute delete

9.05 kB

	{
	"add_bos_token": false,
	"add_prefix_space": false,
	"added_tokens_decoder": {
	"151643": {
	"content": "<\|endoftext\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
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	"151644": {
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	"151651": {
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	"151654": {
	"content": "<\|vision_pad\|>",
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	},
	"151655": {
	"content": "<\|image_pad\|>",
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	},
	"151656": {
	"content": "<\|video_pad\|>",
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	},
	"151657": {
	"content": "<tool_call>",
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	"single_word": false,
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	},
	"151658": {
	"content": "</tool_call>",
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	},
	"151659": {
	"content": "<\|fim_prefix\|>",
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	},
	"151660": {
	"content": "<\|fim_middle\|>",
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	},
	"151661": {
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	"151662": {
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	},
	"151663": {
	"content": "<\|repo_name\|>",
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	},
	"151664": {
	"content": "<\|file_sep\|>",
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	},
	"151665": {
	"content": "<tool_response>",
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	},
	"151666": {
	"content": "</tool_response>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
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	},
	"151667": {
	"content": "<think>",
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	},
	"151668": {
	"content": "</think>",
	"lstrip": false,
	"normalized": false,
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	}
	},
	"additional_special_tokens": [
	"<\|im_start\|>",
	"<\|im_end\|>",
	"<\|object_ref_start\|>",
	"<\|object_ref_end\|>",
	"<\|box_start\|>",
	"<\|box_end\|>",
	"<\|quad_start\|>",
	"<\|quad_end\|>",
	"<\|vision_start\|>",
	"<\|vision_end\|>",
	"<\|vision_pad\|>",
	"<\|image_pad\|>",
	"<\|video_pad\|>"
	],
	"bos_token": null,
	"clean_up_tokenization_spaces": false,
	"eos_token": "<\|im_end\|>",
	"errors": "replace",
	"extra_special_tokens": {},
	"max_length": null,
	"model_max_length": 327680,
	"pad_to_multiple_of": null,
	"pad_token": "<\|endoftext\|>",
	"pad_token_type_id": 0,
	"padding_side": "right",
	"split_special_tokens": false,
	"tokenizer_class": "Qwen2Tokenizer",
	"unk_token": null,
	"chat_template": "{% macro render_content(content) %}{% if content is none %}{{- \"\" }}{% elif content is string %}{{- content }}{% elif content is mapping %}{{- content['value'] if 'value' in content else content['text'] }}{% elif content is iterable %}{% for item in content %}{% if item.type == 'text' %}{{- item['value'] if 'value' in item else item['text'] }}{% elif item.type == 'image' %}<im_patch>{% endif %}{% endfor %}{% endif %}{% endmacro %}{%- if tools %}{{- '<\|im_start\|>system\n' }}{%- if messages[0]['role'] == 'system' %}{{- render_content(messages[0]['content']) }}{%- else %}{{- '' }}{%- endif %}{{- \"\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>\" }}{%- for tool in tools %}{{- \"\n\" }}{{- tool \| tojson }}{%- endfor %}{{- \"\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\n</tool_call><\|im_end\|>\n\" }}{%- else %}{%- if messages[0]['role'] == 'system' %}{{- '<\|im_start\|>system\n' + render_content(messages[0]['content']) + '<\|im_end\|>\n' }}{%- endif %}{%- endif %}{%- for message in messages %}{%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}{{- '<\|im_start\|>' + message.role + '\n' + render_content(message.content) + '<\|im_end\|>' + '\n' }}{%- elif message.role == \"assistant\" %}{%- if loop.last %}{{- '<\|im_start\|>assistant\n<think>\n' + render_content(message.reasoning_content) + '\n</think>\n' + render_content(message.content) }}{%- if message.tool_calls %}{%- for tool_call in message.tool_calls %}{%- set call_details = tool_call.function if tool_call.function is defined else tool_call %}{%- set tool_call_id = tool_call.id if tool_call.id is defined else tool_call.tool_call_id %}{{- '\n<tool_call>\n{\"tool_call_id\": \"' + tool_call_id + '\", \"name\": \"' + call_details.name + '\", \"arguments\": ' }}{% if call_details.arguments is string %}{{- call_details.arguments }}{% else %}{{- call_details.arguments \| tojson }}{% endif %}{{- '}\n</tool_call>' }}{%- endfor %}{%- endif %}{{- '<\|im_end\|>\n' }}{%- else %}{{- '<\|im_start\|>assistant\n' + render_content(message.content) }}{%- if message.tool_calls %}{%- for tool_call in message.tool_calls %}{%- set call_details = tool_call.function if tool_call.function is defined else tool_call %}{%- set tool_call_id = tool_call.id if tool_call.id is defined else tool_call.tool_call_id %}{{- '\n<tool_call>\n{\"tool_call_id\": \"' + tool_call_id + '\", \"name\": \"' + call_details.name + '\", \"arguments\": ' }}{% if call_details.arguments is string %}{{- call_details.arguments }}{% else %}{{- call_details.arguments \| tojson }}{% endif %}{{- '}\n</tool_call>' }}{%- endfor %}{%- endif %}{{- '<\|im_end\|>\n' }}{%- endif %}\n{%- elif message.role in [\"tool_response\", \"tool\"] %}\n {%- if loop.first or loop.previtem.role not in [\"tool\", \"tool_response\"] -%}\n {{- '<\|im_start\|>tool_response\n' -}}\n {%- endif -%}\n {{- '<tool_response>\n' + 'tool_call_id: ' + message.tool_call_id + '\n' + render_content(message.content) + '\n</tool_response>\n' -}}\n {%- if loop.last or loop.nextitem.role not in [\"tool\", \"tool_response\"] -%}\n {{- '<\|im_end\|>\n' -}}\n {%- endif -%}\n{%- endif %}{%- endfor %}{%- if add_generation_prompt %}{{- '<\|im_start\|>assistant\n<think>\n' }}{%- endif %}"
	}