Instructions to use max-zhang/workshop_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use max-zhang/workshop_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="max-zhang/workshop_model")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("max-zhang/workshop_model") model = AutoModelForCausalLM.from_pretrained("max-zhang/workshop_model") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use max-zhang/workshop_model with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "max-zhang/workshop_model" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "max-zhang/workshop_model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/max-zhang/workshop_model
- SGLang
How to use max-zhang/workshop_model 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 "max-zhang/workshop_model" \ --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": "max-zhang/workshop_model", "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 "max-zhang/workshop_model" \ --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": "max-zhang/workshop_model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use max-zhang/workshop_model with Docker Model Runner:
docker model run hf.co/max-zhang/workshop_model
Delete adapter_config.json
Browse files- adapter_config.json +0 -25
adapter_config.json
DELETED
|
@@ -1,25 +0,0 @@
|
|
| 1 |
-
{
|
| 2 |
-
"alpha_pattern": {},
|
| 3 |
-
"auto_mapping": null,
|
| 4 |
-
"base_model_name_or_path": "stabilityai/StableBeluga-7B",
|
| 5 |
-
"bias": "none",
|
| 6 |
-
"fan_in_fan_out": false,
|
| 7 |
-
"inference_mode": true,
|
| 8 |
-
"init_lora_weights": true,
|
| 9 |
-
"layers_pattern": null,
|
| 10 |
-
"layers_to_transform": null,
|
| 11 |
-
"lora_alpha": 16,
|
| 12 |
-
"lora_dropout": 0.1,
|
| 13 |
-
"modules_to_save": null,
|
| 14 |
-
"peft_type": "LORA",
|
| 15 |
-
"r": 64,
|
| 16 |
-
"rank_pattern": {},
|
| 17 |
-
"revision": null,
|
| 18 |
-
"target_modules": [
|
| 19 |
-
"q_proj",
|
| 20 |
-
"v_proj",
|
| 21 |
-
"k_proj",
|
| 22 |
-
"o_proj"
|
| 23 |
-
],
|
| 24 |
-
"task_type": "CAUSAL_LM"
|
| 25 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|