Instructions to use Epimachok/tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Epimachok/tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Epimachok/tiny", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Epimachok/tiny", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Epimachok/tiny with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Epimachok/tiny" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Epimachok/tiny", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Epimachok/tiny
- SGLang
How to use Epimachok/tiny 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 "Epimachok/tiny" \ --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": "Epimachok/tiny", "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 "Epimachok/tiny" \ --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": "Epimachok/tiny", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Epimachok/tiny with Docker Model Runner:
docker model run hf.co/Epimachok/tiny
| { | |
| "_name_or_path": "mini_cpm_russ", | |
| "architectures": [ | |
| "MiniCPMForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_minicpm.MiniCPMConfig", | |
| "AutoModel": "openbmb/MiniCPM-2B-sft-bf16--modeling_minicpm.MiniCPMModel", | |
| "AutoModelForCausalLM": "modeling_minicpm.MiniCPMForCausalLM", | |
| "AutoModelForSeq2SeqLM": "openbmb/MiniCPM-2B-sft-bf16--modeling_minicpm.MiniCPMForCausalLM", | |
| "AutoModelForSequenceClassification": "openbmb/MiniCPM-2B-sft-bf16--modeling_minicpm.MiniCPMForSequenceClassification" | |
| }, | |
| "bos_token_id": 1, | |
| "dim_model_base": 256, | |
| "eos_token_id": 2, | |
| "hidden_act": "silu", | |
| "hidden_size": 2304, | |
| "initializer_range": 0.1, | |
| "intermediate_size": 5760, | |
| "max_position_embeddings": 2048, | |
| "model_type": "minicpm", | |
| "num_attention_heads": 36, | |
| "num_hidden_layers": 40, | |
| "num_key_value_heads": 36, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": null, | |
| "rope_theta": 10000.0, | |
| "scale_depth": 1.4, | |
| "scale_emb": 12, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.39.0.dev0", | |
| "use_cache": true, | |
| "vocab_size": 148106 | |
| } | |