Text Generation
Transformers
Safetensors
qwen2
mergekit
Merge
conversational
text-generation-inference
Instructions to use RDson/CoderO1-DeepSeekR1-Coder-32B-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RDson/CoderO1-DeepSeekR1-Coder-32B-Preview with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="RDson/CoderO1-DeepSeekR1-Coder-32B-Preview") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("RDson/CoderO1-DeepSeekR1-Coder-32B-Preview") model = AutoModelForCausalLM.from_pretrained("RDson/CoderO1-DeepSeekR1-Coder-32B-Preview") 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]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use RDson/CoderO1-DeepSeekR1-Coder-32B-Preview with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "RDson/CoderO1-DeepSeekR1-Coder-32B-Preview" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RDson/CoderO1-DeepSeekR1-Coder-32B-Preview", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/RDson/CoderO1-DeepSeekR1-Coder-32B-Preview
- SGLang
How to use RDson/CoderO1-DeepSeekR1-Coder-32B-Preview 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 "RDson/CoderO1-DeepSeekR1-Coder-32B-Preview" \ --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": "RDson/CoderO1-DeepSeekR1-Coder-32B-Preview", "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 "RDson/CoderO1-DeepSeekR1-Coder-32B-Preview" \ --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": "RDson/CoderO1-DeepSeekR1-Coder-32B-Preview", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use RDson/CoderO1-DeepSeekR1-Coder-32B-Preview with Docker Model Runner:
docker model run hf.co/RDson/CoderO1-DeepSeekR1-Coder-32B-Preview
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base_model:
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- Qwen/Qwen2.5-Coder-32B-Instruct
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library_name: transformers
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tags:
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- mergekit
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- merge
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```
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---
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base_model:
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- deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
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- Qwen/Qwen2.5-Coder-32B-Instruct
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- Qwen/Qwen2.5-32B
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library_name: transformers
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tags:
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- mergekit
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- merge
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language:
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- zho
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- eng
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- fra
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- spa
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- por
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---
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# FuseAI uploaded their own Coder model here: [FuseAI/FuseO1-DeepSeekR1-Qwen2.5-Coder-32B-Preview](https://huggingface.co/FuseAI/FuseO1-DeepSeekR1-Qwen2.5-Coder-32B-Preview).
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GGUF files: [RDson/CoderO1-DeepSeekR1-Coder-32B-Preview-GGUF](https://huggingface.co/RDson/CoderO1-DeepSeekR1-Coder-32B-Preview-GGUF).
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*This is based on the works of [FuseAI/FuseO1-Preview](https://huggingface.co/collections/FuseAI/fuseo1-preview-678eb56093649b2688bc9977).*
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# CoderO1-DeepSeekR1-Coder-32B-Preview
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the sce merge method using [Qwen/Qwen2.5-32B](https://huggingface.co/Qwen/Qwen2.5-32B) as a base.
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### Models Merged
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The following models were included in the merge:
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* [deepseek-ai/DeepSeek-R1-Distill-Qwen-32B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B)
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* [Qwen/Qwen2.5-Coder-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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models:
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# Pivot model
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- model: Qwen/Qwen2.5-32B
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# Target models
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- model: Qwen/Qwen2.5-Coder-32B-Instruct
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- model: deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
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merge_method: sce
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base_model: Qwen/Qwen2.5-32B
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parameters:
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select_topk: 1.0
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dtype: bfloat16
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```
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