Instructions to use dusersad12/BestRewardModel-TestRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/BestRewardModel-TestRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="dusersad12/BestRewardModel-TestRepo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("dusersad12/BestRewardModel-TestRepo") model = AutoModelForCausalLM.from_pretrained("dusersad12/BestRewardModel-TestRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use dusersad12/BestRewardModel-TestRepo with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "dusersad12/BestRewardModel-TestRepo" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dusersad12/BestRewardModel-TestRepo", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/dusersad12/BestRewardModel-TestRepo
- SGLang
How to use dusersad12/BestRewardModel-TestRepo 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 "dusersad12/BestRewardModel-TestRepo" \ --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": "dusersad12/BestRewardModel-TestRepo", "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 "dusersad12/BestRewardModel-TestRepo" \ --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": "dusersad12/BestRewardModel-TestRepo", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use dusersad12/BestRewardModel-TestRepo with Docker Model Runner:
docker model run hf.co/dusersad12/BestRewardModel-TestRepo
Upload config.json with huggingface_hub
Browse files- config.json +7 -0
config.json
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"model_type": "gpt2",
|
| 3 |
+
"architectures": ["GPT2LMHeadModel"],
|
| 4 |
+
"n_layer": 36,
|
| 5 |
+
"n_head": 20,
|
| 6 |
+
"n_embd": 1280
|
| 7 |
+
}
|