Text Generation
Transformers
Safetensors
text generation
Deci AI
DeciCoder
custom_code
Eval Results (legacy)
Instructions to use Deci/DeciCoder-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Deci/DeciCoder-1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Deci/DeciCoder-1b", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Deci/DeciCoder-1b", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Deci/DeciCoder-1b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Deci/DeciCoder-1b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Deci/DeciCoder-1b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Deci/DeciCoder-1b
- SGLang
How to use Deci/DeciCoder-1b 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 "Deci/DeciCoder-1b" \ --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": "Deci/DeciCoder-1b", "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 "Deci/DeciCoder-1b" \ --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": "Deci/DeciCoder-1b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Deci/DeciCoder-1b with Docker Model Runner:
docker model run hf.co/Deci/DeciCoder-1b
safetensors, config changes (#12)
Browse files- config change (8fe3c20c15244fa0565f8e27b6c512c55a874adb)
- safetensors (eb3b3826e268aed7924188dc744498be6d4ae9fc)
- config.json +1 -2
- configuration_decicoder.py +0 -1
- pytorch_model.bin → model.safetensors +2 -2
config.json
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@@ -1,6 +1,6 @@
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{
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"architectures": [
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"
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],
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"auto_map": {
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"AutoConfig": "configuration_decicoder.DeciCoderConfig",
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"initializer_range": 0.02,
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"intermediate_size": 5888,
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"max_position_embeddings": 2048,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 20,
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"num_key_value_heads": 4,
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{
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"architectures": [
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"DeciCoderForCausalLM"
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],
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"auto_map": {
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"AutoConfig": "configuration_decicoder.DeciCoderConfig",
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"initializer_range": 0.02,
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"intermediate_size": 5888,
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"max_position_embeddings": 2048,
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"num_attention_heads": 32,
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"num_hidden_layers": 20,
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"num_key_value_heads": 4,
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configuration_decicoder.py
CHANGED
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```"""
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model_type = "llama"
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keys_to_ignore_at_inference = ["past_key_values"]
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def __init__(
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```"""
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keys_to_ignore_at_inference = ["past_key_values"]
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def __init__(
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pytorch_model.bin → model.safetensors
RENAMED
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:510256faa3d388cad1dcbc30c39d32f9289410a399f4c0435bec27ec135c6f0f
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size 2227364400
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