Instructions to use blueapple8259/test_model1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use blueapple8259/test_model1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="blueapple8259/test_model1")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("blueapple8259/test_model1") model = AutoModelForCausalLM.from_pretrained("blueapple8259/test_model1") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use blueapple8259/test_model1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "blueapple8259/test_model1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "blueapple8259/test_model1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/blueapple8259/test_model1
- SGLang
How to use blueapple8259/test_model1 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 "blueapple8259/test_model1" \ --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": "blueapple8259/test_model1", "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 "blueapple8259/test_model1" \ --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": "blueapple8259/test_model1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use blueapple8259/test_model1 with Docker Model Runner:
docker model run hf.co/blueapple8259/test_model1
Commit ·
4e1233d
1
Parent(s): 0d55a8f
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,3 +1,8 @@
|
|
| 1 |
---
|
| 2 |
license: cc-by-nc-sa-2.0
|
|
|
|
|
|
|
|
|
|
|
|
|
| 3 |
---
|
|
|
|
|
|
| 1 |
---
|
| 2 |
license: cc-by-nc-sa-2.0
|
| 3 |
+
datasets:
|
| 4 |
+
- maywell/ko_wikidata_QA
|
| 5 |
+
language:
|
| 6 |
+
- ko
|
| 7 |
---
|
| 8 |
+
[maywell/ko_wikidata_QA](https://huggingface.co/datasets/maywell/ko_wikidata_QA)데이터셋의 output만 사용해서 학습하였으며 영어는 지원 안 됩니다.
|