Instructions to use canbingol/DeepSeek-R1-Descartes-COT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use canbingol/DeepSeek-R1-Descartes-COT with Transformers:

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

pipe = pipeline("text-generation", model="canbingol/DeepSeek-R1-Descartes-COT")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("canbingol/DeepSeek-R1-Descartes-COT")
model = AutoModelForCausalLM.from_pretrained("canbingol/DeepSeek-R1-Descartes-COT")
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

vLLM

How to use canbingol/DeepSeek-R1-Descartes-COT with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "canbingol/DeepSeek-R1-Descartes-COT"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "canbingol/DeepSeek-R1-Descartes-COT",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/canbingol/DeepSeek-R1-Descartes-COT

SGLang

How to use canbingol/DeepSeek-R1-Descartes-COT 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 "canbingol/DeepSeek-R1-Descartes-COT" \
    --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": "canbingol/DeepSeek-R1-Descartes-COT",
		"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 "canbingol/DeepSeek-R1-Descartes-COT" \
        --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": "canbingol/DeepSeek-R1-Descartes-COT",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio new

How to use canbingol/DeepSeek-R1-Descartes-COT 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 canbingol/DeepSeek-R1-Descartes-COT 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 canbingol/DeepSeek-R1-Descartes-COT to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for canbingol/DeepSeek-R1-Descartes-COT to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="canbingol/DeepSeek-R1-Descartes-COT",
    max_seq_length=2048,
)

Docker Model Runner
How to use canbingol/DeepSeek-R1-Descartes-COT with Docker Model Runner:
```
docker model run hf.co/canbingol/DeepSeek-R1-Descartes-COT
```

canbingol commited on Feb 3, 2025

Commit

48d8284

verified ·

1 Parent(s): 405d57a

Upload model trained with Unsloth

Browse files

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Files changed (6) hide show

README.md +1 -0
config.json +51 -0
generation_config.json +11 -0
model-00001-of-00002.safetensors +3 -0
model-00002-of-00002.safetensors +3 -0
model.safetensors.index.json +0 -0

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@@ -6,6 +6,7 @@ tags:
 - unsloth
 - llama
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 license: apache-2.0
 language:
 - en

 - unsloth
 - llama
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+- sft
 license: apache-2.0
 language:
 - en

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+    "rope_type": "llama3"
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+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.48.2",
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+  "use_cache": true,
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+}

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+  "temperature": 0.6,
+  "top_p": 0.95,
+  "transformers_version": "4.48.2"
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