Instructions to use BigSalmon/PointsOneSent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BigSalmon/PointsOneSent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="BigSalmon/PointsOneSent")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("BigSalmon/PointsOneSent") model = AutoModelForCausalLM.from_pretrained("BigSalmon/PointsOneSent") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use BigSalmon/PointsOneSent with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "BigSalmon/PointsOneSent" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "BigSalmon/PointsOneSent", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/BigSalmon/PointsOneSent
- SGLang
How to use BigSalmon/PointsOneSent 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 "BigSalmon/PointsOneSent" \ --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": "BigSalmon/PointsOneSent", "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 "BigSalmon/PointsOneSent" \ --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": "BigSalmon/PointsOneSent", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use BigSalmon/PointsOneSent with Docker Model Runner:
docker model run hf.co/BigSalmon/PointsOneSent
File size: 595 Bytes
515fe1d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/PointsOneSent")
model = AutoModelForCausalLM.from_pretrained("BigSalmon/PointsOneSent")
```
```
- moviepass to return
- this summer
- swooped up by
- original co-founder stacy spikes
text: the re-launch of moviepass is set to transpire this summer, ( rescued at the hands of / under the stewardship of / spearheaded by ) its founding father, stacy spikes.
***
-
```
It should also be able to do all that this can: https://huggingface.co/BigSalmon/InformalToFormalLincoln27 |