Instructions to use prithivMLmods/Codepy-Deepthink-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use prithivMLmods/Codepy-Deepthink-3B with Transformers:

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

pipe = pipeline("text-generation", model="prithivMLmods/Codepy-Deepthink-3B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("prithivMLmods/Codepy-Deepthink-3B")
model = AutoModelForCausalLM.from_pretrained("prithivMLmods/Codepy-Deepthink-3B", device_map="auto")
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=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use prithivMLmods/Codepy-Deepthink-3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "prithivMLmods/Codepy-Deepthink-3B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prithivMLmods/Codepy-Deepthink-3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/prithivMLmods/Codepy-Deepthink-3B

SGLang

How to use prithivMLmods/Codepy-Deepthink-3B 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 "prithivMLmods/Codepy-Deepthink-3B" \
    --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": "prithivMLmods/Codepy-Deepthink-3B",
		"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 "prithivMLmods/Codepy-Deepthink-3B" \
        --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": "prithivMLmods/Codepy-Deepthink-3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use prithivMLmods/Codepy-Deepthink-3B with Docker Model Runner:
```
docker model run hf.co/prithivMLmods/Codepy-Deepthink-3B
```

prithivMLmods commited on Dec 26, 2024

Commit

9e3bb69

verified ·

1 Parent(s): f05703a

Update README.md

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README.md +19 -0

README.md CHANGED Viewed

@@ -13,4 +13,23 @@ tags:
 - ollama
 - llama-cpp
 - trl
 ---

 - ollama
 - llama-cpp
 - trl
+---
+# Codepy 3B Deep Think Model File
+| **File Name**                     | **Size**       | **Description**                                 | **Upload Status** |
+|-----------------------------------|----------------|------------------------------------------------|-------------------|
+| `.gitattributes`                  | 1.57 kB        | Git LFS configuration for large files.          | Uploaded          |
+| `README.md`                       | 221 Bytes      | Basic repository information.                   | Updated           |
+| `config.json`                     | 994 Bytes      | Model configuration with architectural details. | Uploaded          |
+| `generation_config.json`          | 248 Bytes      | Default generation parameters.                  | Uploaded          |
+| `pytorch_model-00001-of-00002.bin`| 4.97 GB        | Sharded PyTorch model weights (part 1 of 2).    | Uploaded (LFS)    |
+| `pytorch_model-00002-of-00002.bin`| 1.46 GB        | Sharded PyTorch model weights (part 2 of 2).    | Uploaded (LFS)    |
+| `pytorch_model.bin.index.json`    | 21.2 kB        | Index file mapping model shards.                | Uploaded          |
+| `special_tokens_map.json`         | 477 Bytes      | Maps special tokens to their respective IDs.    | Uploaded          |
+| `tokenizer.json`                  | 17.2 MB        | Full tokenizer vocabulary and merges.           | Uploaded (LFS)    |
+| `tokenizer_config.json`           | 57.5 kB        | Tokenizer configuration details.                | Uploaded          |
 ---