Instructions to use mrm8488/Alpacoom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/Alpacoom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mrm8488/Alpacoom")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mrm8488/Alpacoom", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use mrm8488/Alpacoom with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mrm8488/Alpacoom" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mrm8488/Alpacoom", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/mrm8488/Alpacoom
- SGLang
How to use mrm8488/Alpacoom 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 "mrm8488/Alpacoom" \ --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": "mrm8488/Alpacoom", "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 "mrm8488/Alpacoom" \ --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": "mrm8488/Alpacoom", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use mrm8488/Alpacoom with Docker Model Runner:
docker model run hf.co/mrm8488/Alpacoom
Update README.md
Browse files
README.md
CHANGED
|
@@ -16,7 +16,7 @@ datasets:
|
|
| 16 |
|
| 17 |
|
| 18 |
## Adapter Description
|
| 19 |
-
This adapter was created
|
| 20 |
|
| 21 |
## Model Description
|
| 22 |
BigScience Large Open-science Open-access Multilingual Language Model
|
|
|
|
| 16 |
|
| 17 |
|
| 18 |
## Adapter Description
|
| 19 |
+
This adapter was created with the [PEFT](https://github.com/huggingface/peft) library and allowed the base model **BigScience/BLOOM 7B1** to be fine-tuned on the **Stanford's Alpaca Dataset** by using the method **LoRA**.
|
| 20 |
|
| 21 |
## Model Description
|
| 22 |
BigScience Large Open-science Open-access Multilingual Language Model
|