Text Generation
Transformers
English
seq2seq
Merge
mergekit
lazymergekit
Or4cl3-1/code-slerp
Or4cl3-1/SAM-Gemini-BLOOM-OPT-Gopher-Megatron-slerp
Instructions to use Or4cl3-1/Daedalus_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Or4cl3-1/Daedalus_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Or4cl3-1/Daedalus_1")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Or4cl3-1/Daedalus_1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Or4cl3-1/Daedalus_1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Or4cl3-1/Daedalus_1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Or4cl3-1/Daedalus_1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Or4cl3-1/Daedalus_1
- SGLang
How to use Or4cl3-1/Daedalus_1 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 "Or4cl3-1/Daedalus_1" \ --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": "Or4cl3-1/Daedalus_1", "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 "Or4cl3-1/Daedalus_1" \ --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": "Or4cl3-1/Daedalus_1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Or4cl3-1/Daedalus_1 with Docker Model Runner:
docker model run hf.co/Or4cl3-1/Daedalus_1
Update training_args.json
Browse files- training_args.json +1 -1
training_args.json
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"output_dir": "./results",
|
| 3 |
-
"overwrite_output_dir":
|
| 4 |
"max_steps": 200000,
|
| 5 |
"per_device_train_batch_size": 32,
|
| 6 |
"per_device_eval_batch_size": 32,
|
|
|
|
| 1 |
{
|
| 2 |
"output_dir": "./results",
|
| 3 |
+
"overwrite_output_dir": True,
|
| 4 |
"max_steps": 200000,
|
| 5 |
"per_device_train_batch_size": 32,
|
| 6 |
"per_device_eval_batch_size": 32,
|