Instructions to use maicomputer/alpaca-native with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maicomputer/alpaca-native with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="maicomputer/alpaca-native")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("maicomputer/alpaca-native") model = AutoModelForCausalLM.from_pretrained("maicomputer/alpaca-native", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use maicomputer/alpaca-native with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "maicomputer/alpaca-native" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "maicomputer/alpaca-native", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/maicomputer/alpaca-native
- SGLang
How to use maicomputer/alpaca-native 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 "maicomputer/alpaca-native" \ --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": "maicomputer/alpaca-native", "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 "maicomputer/alpaca-native" \ --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": "maicomputer/alpaca-native", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use maicomputer/alpaca-native with Docker Model Runner:
docker model run hf.co/maicomputer/alpaca-native
Delete checkpoint-200
Browse files- checkpoint-200/added_tokens.json +0 -3
- checkpoint-200/config.json +0 -23
- checkpoint-200/generation_config.json +0 -7
- checkpoint-200/optimizer.pt +0 -3
- checkpoint-200/pytorch_model-00001-of-00003.bin +0 -3
- checkpoint-200/pytorch_model-00002-of-00003.bin +0 -3
- checkpoint-200/pytorch_model-00003-of-00003.bin +0 -3
- checkpoint-200/pytorch_model.bin.index.json +0 -330
- checkpoint-200/rng_state_0.pth +0 -3
- checkpoint-200/rng_state_1.pth +0 -3
- checkpoint-200/rng_state_2.pth +0 -3
- checkpoint-200/rng_state_3.pth +0 -3
- checkpoint-200/scheduler.pt +0 -3
- checkpoint-200/special_tokens_map.json +0 -6
- checkpoint-200/tokenizer.model +0 -3
- checkpoint-200/tokenizer_config.json +0 -9
- checkpoint-200/trainer_state.json +0 -1216
- checkpoint-200/training_args.bin +0 -3
checkpoint-200/added_tokens.json
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checkpoint-200/training_args.bin
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:489a2c2f2f6410389af7de61eb98d5f872555fc9d4010f24177144678ba20982
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| 3 |
-
size 3707
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