Text Generation
Transformers
PyTorch
English
code
codegen
Diff Model
causal-lm
code-generation
The Pile
Instructions to use CarperAI/diff-codegen-350m-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CarperAI/diff-codegen-350m-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CarperAI/diff-codegen-350m-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("CarperAI/diff-codegen-350m-v2") model = AutoModelForCausalLM.from_pretrained("CarperAI/diff-codegen-350m-v2") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use CarperAI/diff-codegen-350m-v2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CarperAI/diff-codegen-350m-v2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CarperAI/diff-codegen-350m-v2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/CarperAI/diff-codegen-350m-v2
- SGLang
How to use CarperAI/diff-codegen-350m-v2 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 "CarperAI/diff-codegen-350m-v2" \ --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": "CarperAI/diff-codegen-350m-v2", "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 "CarperAI/diff-codegen-350m-v2" \ --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": "CarperAI/diff-codegen-350m-v2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use CarperAI/diff-codegen-350m-v2 with Docker Model Runner:
docker model run hf.co/CarperAI/diff-codegen-350m-v2
Upload config.json
#7
by HyperionHF - opened
- config.json +42 -0
config.json
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{
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"_name_or_path": "codegen-350",
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"activation_function": "gelu_new",
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"architectures": [
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"CodeGenForCausalLM"
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],
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"attn_pdrop": 0.0,
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"bos_token_id": 1,
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"embd_pdrop": 0.0,
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"eos_token_id": 50256,
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"gradient_checkpointing": false,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"model_type": "codegen",
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"n_ctx": 2048,
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"n_embd": 1024,
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"n_head": 16,
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"n_inner": null,
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"n_layer": 20,
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"n_positions": 2048,
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"resid_pdrop": 0.0,
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"rotary_dim": 32,
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"scale_attn_weights": true,
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"summary_activation": null,
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"summary_first_dropout": 0.1,
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"task_specific_params": {
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"text-generation": {
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"do_sample": true,
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"max_length": 50,
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"temperature": 1.0
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}
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},
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"tie_word_embeddings": false,
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"tokenizer_class": "GPT2Tokenizer",
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"torch_dtype": "float16",
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"transformers_version": "4.22.0.dev0",
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"use_cache": false,
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"vocab_size": 50295
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}
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