Text Generation
Transformers
Safetensors
English
cloverlm
causal-lm
quartet-ii
nvfp4
low-precision-training
pretrained
custom_code
Instructions to use daslab-testing/CloverLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use daslab-testing/CloverLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="daslab-testing/CloverLM", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("daslab-testing/CloverLM", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use daslab-testing/CloverLM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "daslab-testing/CloverLM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "daslab-testing/CloverLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/daslab-testing/CloverLM
- SGLang
How to use daslab-testing/CloverLM 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 "daslab-testing/CloverLM" \ --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": "daslab-testing/CloverLM", "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 "daslab-testing/CloverLM" \ --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": "daslab-testing/CloverLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use daslab-testing/CloverLM with Docker Model Runner:
docker model run hf.co/daslab-testing/CloverLM
| { | |
| "architectures": [ | |
| "CloverLMForCausalLM" | |
| ], | |
| "attn_backend": "pytorch", | |
| "auto_map": { | |
| "AutoConfig": "configuration_cloverlm.CloverLMConfig", | |
| "AutoModelForCausalLM": "modeling_cloverlm.CloverLMForCausalLM", | |
| "AutoTokenizer": [ | |
| "tokenization_cloverlm.CloverLMTokenizer", | |
| null | |
| ] | |
| }, | |
| "d_head": 128, | |
| "dtype": "bfloat16", | |
| "head_dim": 128, | |
| "heads": 28, | |
| "hidden_size": 3584, | |
| "intermediate_size": 14336, | |
| "max_context": 1024, | |
| "max_position_embeddings": 1024, | |
| "model_type": "cloverlm", | |
| "num_attention_heads": 28, | |
| "num_blocks": 29, | |
| "num_hidden_layers": 29, | |
| "num_key_value_heads": 7, | |
| "quartet_2_impl": "pseudoquant", | |
| "ratio": 4, | |
| "scale_type": "1/sqrt(d)", | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.4.0", | |
| "vocab_size": 32000, | |
| "weight_tying": true | |
| } | |