Instructions to use GreenBitAI/LLaMA-7B-2bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GreenBitAI/LLaMA-7B-2bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="GreenBitAI/LLaMA-7B-2bit")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("GreenBitAI/LLaMA-7B-2bit") model = AutoModelForCausalLM.from_pretrained("GreenBitAI/LLaMA-7B-2bit") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use GreenBitAI/LLaMA-7B-2bit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GreenBitAI/LLaMA-7B-2bit" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GreenBitAI/LLaMA-7B-2bit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/GreenBitAI/LLaMA-7B-2bit
- SGLang
How to use GreenBitAI/LLaMA-7B-2bit 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 "GreenBitAI/LLaMA-7B-2bit" \ --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": "GreenBitAI/LLaMA-7B-2bit", "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 "GreenBitAI/LLaMA-7B-2bit" \ --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": "GreenBitAI/LLaMA-7B-2bit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use GreenBitAI/LLaMA-7B-2bit with Docker Model Runner:
docker model run hf.co/GreenBitAI/LLaMA-7B-2bit
Joseph Bethge commited on
Commit ·
375fcd2
1
Parent(s): bc349b8
add 2-bit llama model
Browse files- config.json +19 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- tokenizer.model +3 -0
- tokenizer_config.json +7 -0
config.json
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{
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"architectures": ["LlamaForCausalLM"],
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"bos_token_id": 0,
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"eos_token_id": 1,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"intermediate_size": 11008,
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"initializer_range": 0.02,
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"max_sequence_length": 2048,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"pad_token_id": -1,
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"rms_norm_eps": 1e-06,
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"torch_dtype": "float16",
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"transformers_version": "4.27.0.dev0",
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"use_cache": true,
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"vocab_size": 32000
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:56ac29638ed96a1f3da3da1618b6ac83bcfd3d933bdb9673b89b7242898b5a52
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size 2410179115
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special_tokens_map.json
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{}
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
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size 499723
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tokenizer_config.json
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{
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"bos_token": "",
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"eos_token": "",
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"model_max_length": 1000000000000000019884624838656,
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": ""
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}
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