Instructions to use dgnk007/crow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dgnk007/crow with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="dgnk007/crow")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("dgnk007/crow") model = AutoModelForCausalLM.from_pretrained("dgnk007/crow") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use dgnk007/crow with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "dgnk007/crow" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dgnk007/crow", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/dgnk007/crow
- SGLang
How to use dgnk007/crow 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 "dgnk007/crow" \ --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": "dgnk007/crow", "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 "dgnk007/crow" \ --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": "dgnk007/crow", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use dgnk007/crow with Docker Model Runner:
docker model run hf.co/dgnk007/crow
Upload model
Browse files- config.json +3 -1
- generation_config.json +2 -0
- pytorch_model.bin +1 -1
config.json
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"_name_or_path": "
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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],
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"attn_pdrop": 0.1,
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"bos_token_id": 50256,
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"embd_pdrop": 0.1,
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"eos_token_id": 50256,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"model_type": "gpt2",
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"n_ctx": 1024,
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"n_embd": 768,
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"_name_or_path": "./results",
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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],
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"attn_pdrop": 0.1,
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"bos_token_id": 50256,
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"do_sample": true,
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"embd_pdrop": 0.1,
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"eos_token_id": 50256,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"max_length": 50,
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"model_type": "gpt2",
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"n_ctx": 1024,
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"n_embd": 768,
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generation_config.json
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"bos_token_id": 50256,
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"eos_token_id": 50256,
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"transformers_version": "4.30.2"
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"_from_model_config": true,
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"do_sample": true,
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"max_length": 50,
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"transformers_version": "4.30.2"
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}
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pytorch_model.bin
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size 497807197
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version https://git-lfs.github.com/spec/v1
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size 497807197
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