Instructions to use echo840/Monkey-Chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use echo840/Monkey-Chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="echo840/Monkey-Chat", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("echo840/Monkey-Chat", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use echo840/Monkey-Chat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "echo840/Monkey-Chat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "echo840/Monkey-Chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/echo840/Monkey-Chat
- SGLang
How to use echo840/Monkey-Chat 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 "echo840/Monkey-Chat" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "echo840/Monkey-Chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "echo840/Monkey-Chat" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "echo840/Monkey-Chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use echo840/Monkey-Chat with Docker Model Runner:
docker model run hf.co/echo840/Monkey-Chat
Update tokenization_qwen.py
#1
by pbaylies - opened
- tokenization_qwen.py +1 -1
tokenization_qwen.py
CHANGED
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@@ -111,7 +111,6 @@ class QWenTokenizer(PreTrainedTokenizer):
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quad_end_tag='</quad>',
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**kwargs,
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):
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-
super().__init__(**kwargs)
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self.image_start_tag = image_start_tag
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self.image_end_tag = image_end_tag
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self.image_pad_tag = image_pad_tag
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@@ -128,6 +127,7 @@ class QWenTokenizer(PreTrainedTokenizer):
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image_start_tag, image_end_tag,
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image_pad_tag
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)
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self.errors = errors # how to handle errors in decoding
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quad_end_tag='</quad>',
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**kwargs,
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):
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self.image_start_tag = image_start_tag
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self.image_end_tag = image_end_tag
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self.image_pad_tag = image_pad_tag
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image_start_tag, image_end_tag,
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image_pad_tag
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)
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+
super().__init__(**kwargs)
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self.errors = errors # how to handle errors in decoding
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