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
Upload folder using huggingface_hub
Browse files- config.json +4 -1
- tokenizer_config.json +4 -1
config.json
CHANGED
|
@@ -6,7 +6,10 @@
|
|
| 6 |
"auto_map": {
|
| 7 |
"AutoConfig": "configuration_cloverlm.CloverLMConfig",
|
| 8 |
"AutoModelForCausalLM": "modeling_cloverlm.CloverLMForCausalLM",
|
| 9 |
-
"AutoTokenizer":
|
|
|
|
|
|
|
|
|
|
| 10 |
},
|
| 11 |
"d_head": 128,
|
| 12 |
"heads": 28,
|
|
|
|
| 6 |
"auto_map": {
|
| 7 |
"AutoConfig": "configuration_cloverlm.CloverLMConfig",
|
| 8 |
"AutoModelForCausalLM": "modeling_cloverlm.CloverLMForCausalLM",
|
| 9 |
+
"AutoTokenizer": [
|
| 10 |
+
"tokenization_cloverlm.CloverLMTokenizer",
|
| 11 |
+
null
|
| 12 |
+
]
|
| 13 |
},
|
| 14 |
"d_head": 128,
|
| 15 |
"heads": 28,
|
tokenizer_config.json
CHANGED
|
@@ -1,7 +1,10 @@
|
|
| 1 |
{
|
| 2 |
"tokenizer_class": "CloverLMTokenizer",
|
| 3 |
"auto_map": {
|
| 4 |
-
"AutoTokenizer":
|
|
|
|
|
|
|
|
|
|
| 5 |
},
|
| 6 |
"use_fast": false
|
| 7 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"tokenizer_class": "CloverLMTokenizer",
|
| 3 |
"auto_map": {
|
| 4 |
+
"AutoTokenizer": [
|
| 5 |
+
"tokenization_cloverlm.CloverLMTokenizer",
|
| 6 |
+
null
|
| 7 |
+
]
|
| 8 |
},
|
| 9 |
"use_fast": false
|
| 10 |
}
|