Instructions to use aframson/RDPD-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aframson/RDPD-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="aframson/RDPD-mini", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("aframson/RDPD-mini", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use aframson/RDPD-mini with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "aframson/RDPD-mini" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "aframson/RDPD-mini", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/aframson/RDPD-mini
- SGLang
How to use aframson/RDPD-mini 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 "aframson/RDPD-mini" \ --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": "aframson/RDPD-mini", "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 "aframson/RDPD-mini" \ --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": "aframson/RDPD-mini", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use aframson/RDPD-mini with Docker Model Runner:
docker model run hf.co/aframson/RDPD-mini
asas
Browse files- config.json +24 -0
- pytorch_model.bin +3 -0
config.json
ADDED
|
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"OBILanguageModel"
|
| 4 |
+
],
|
| 5 |
+
"auto_map": {
|
| 6 |
+
"AutoConfig": "modelConfig.OBIConfig",
|
| 7 |
+
"AutoModel": "modelLM.OBILanguageModel",
|
| 8 |
+
"AutoModelForCausalLM": "modelLM.OBILanguageModel",
|
| 9 |
+
"AutoModelForQuestionAnswering": "modelLM.OBILanguageModel"
|
| 10 |
+
},
|
| 11 |
+
"batch_size": 50,
|
| 12 |
+
"block_size": 256,
|
| 13 |
+
"device": "cpu",
|
| 14 |
+
"eval_interval": 100,
|
| 15 |
+
"hidden_dropout_prob": 0.1,
|
| 16 |
+
"hidden_size": 108,
|
| 17 |
+
"learning_rate": 0.001,
|
| 18 |
+
"max_iters": 8000,
|
| 19 |
+
"num_attention_heads": 12,
|
| 20 |
+
"num_hidden_layers": 10,
|
| 21 |
+
"torch_dtype": "float32",
|
| 22 |
+
"transformers_version": "4.30.2",
|
| 23 |
+
"vocab_size": 1000
|
| 24 |
+
}
|
pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:56e6c462599554351e24c9230eac664dd723ece4d06a83edd5f04ea71feab9ef
|
| 3 |
+
size 14276973
|