Instructions to use IvanD2002/falcon7binstruct_stuco_task with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IvanD2002/falcon7binstruct_stuco_task with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="IvanD2002/falcon7binstruct_stuco_task")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("IvanD2002/falcon7binstruct_stuco_task", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use IvanD2002/falcon7binstruct_stuco_task with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "IvanD2002/falcon7binstruct_stuco_task"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IvanD2002/falcon7binstruct_stuco_task",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/IvanD2002/falcon7binstruct_stuco_task

SGLang

How to use IvanD2002/falcon7binstruct_stuco_task 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 "IvanD2002/falcon7binstruct_stuco_task" \
    --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": "IvanD2002/falcon7binstruct_stuco_task",
		"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 "IvanD2002/falcon7binstruct_stuco_task" \
        --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": "IvanD2002/falcon7binstruct_stuco_task",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use IvanD2002/falcon7binstruct_stuco_task with Docker Model Runner:
```
docker model run hf.co/IvanD2002/falcon7binstruct_stuco_task
```

IvanD2002 commited on Apr 10, 2024

Commit

1ee3fe4

verified ·

1 Parent(s): abdc322

Training in progress, step 20

Browse files

Files changed (2) hide show

adapter_model.safetensors +1 -1
runs/Apr10_13-25-28_98425f0a4805/events.out.tfevents.1712755544.98425f0a4805.1289.0 +2 -2

adapter_model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8554222ba3bb0f1fdc5cfc35f423e7d2076a1c5f9de8f5b3e8c4ff8402468210
 size 261131840

 version https://git-lfs.github.com/spec/v1
+oid sha256:13fe6150a64a4b3df93f131ddefe5bb4c5d838e1417fee3c52b88441a81c3a85
 size 261131840

runs/Apr10_13-25-28_98425f0a4805/events.out.tfevents.1712755544.98425f0a4805.1289.0 CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0eecb820883269f226fb038a374b460a3d5612aa7b255f752fdf02239d0bb4da
-size 5967

 version https://git-lfs.github.com/spec/v1
+oid sha256:a42d4b7e84d06c8f46ac3ec93f39face52a7359c3f2edbfb3ff6be9f6adc5983
+size 6522