Instructions to use mrm8488/Alpacoom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/Alpacoom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mrm8488/Alpacoom")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mrm8488/Alpacoom", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use mrm8488/Alpacoom with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mrm8488/Alpacoom" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mrm8488/Alpacoom", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/mrm8488/Alpacoom
- SGLang
How to use mrm8488/Alpacoom 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 "mrm8488/Alpacoom" \ --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": "mrm8488/Alpacoom", "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 "mrm8488/Alpacoom" \ --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": "mrm8488/Alpacoom", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use mrm8488/Alpacoom with Docker Model Runner:
docker model run hf.co/mrm8488/Alpacoom
Getting size mismatch error while loading the peft modal
RuntimeError: Error(s) in loading state_dict for PeftModelForCausalLM:
size mismatch for base_model.model.transformer.h.0.self_attention.query_key_value.lora_A.default.weight: copying a param with shape torch.Size([32, 4096]) from checkpoint, the shape in current model is torch.Size([16, 4096]).
size mismatch for base_model.model.transformer.h.0.self_attention.query_key_value.lora_B.default.weight: copying a param with shape torch.Size([8192, 16, 1]) from checkpoint, the shape in current model is torch.Size([12288, 16]).
size mismatch for base_model.model.transformer.h.1.self_attention.query_key_value.lora_A.default.weight: copying a param with shape torch.Size([32, 4096]) from checkpoint, the shape in current model is torch.Size([16, 4096]).
size mismatch for base_model.model.transformer.h.1.self_attention.query_key_value.lora_B.default.weight: copying a param with shape torch.Size([8192, 16, 1]) from checkpoint, the shape in current model is torch.Size([12288, 16]).
size mismatch for base_model.model.transformer.h.2.self_attention.query_key_value.lora_A.default.weight: copying a param