Instructions to use gjonesQ02/ScopeOfWorkTextGenerator_Alpha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use gjonesQ02/ScopeOfWorkTextGenerator_Alpha with Transformers:

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

pipe = pipeline("text-generation", model="gjonesQ02/ScopeOfWorkTextGenerator_Alpha")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("gjonesQ02/ScopeOfWorkTextGenerator_Alpha")
model = AutoModelForCausalLM.from_pretrained("gjonesQ02/ScopeOfWorkTextGenerator_Alpha", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use gjonesQ02/ScopeOfWorkTextGenerator_Alpha with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "gjonesQ02/ScopeOfWorkTextGenerator_Alpha"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "gjonesQ02/ScopeOfWorkTextGenerator_Alpha",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/gjonesQ02/ScopeOfWorkTextGenerator_Alpha

SGLang

How to use gjonesQ02/ScopeOfWorkTextGenerator_Alpha 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 "gjonesQ02/ScopeOfWorkTextGenerator_Alpha" \
    --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": "gjonesQ02/ScopeOfWorkTextGenerator_Alpha",
		"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 "gjonesQ02/ScopeOfWorkTextGenerator_Alpha" \
        --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": "gjonesQ02/ScopeOfWorkTextGenerator_Alpha",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use gjonesQ02/ScopeOfWorkTextGenerator_Alpha with Docker Model Runner:
```
docker model run hf.co/gjonesQ02/ScopeOfWorkTextGenerator_Alpha
```

gjonesQ02 commited on Jun 8, 2024

Commit

bbaff50

verified ·

1 Parent(s): 2b857ac

Training in progress, step 3000

Browse files

Files changed (2) hide show

model.safetensors +1 -1
runs/Jun08_19-43-36_viridian/events.out.tfevents.1717875819.viridian.2375457.2 +2 -2

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4f84f987d160b96016eeaa3de541a53194b267fdd094a17560c4e1e7585ff855
 size 327657928

 version https://git-lfs.github.com/spec/v1
+oid sha256:69bd95fc7eb00fa94a9e34662a49e80830a2a1d708f34ddb5e7f01ea6209ad7f
 size 327657928

runs/Jun08_19-43-36_viridian/events.out.tfevents.1717875819.viridian.2375457.2 CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:95fedb27d135f5037fc0c8ef9678474b5fc4a68cc549d3585a5cee5be2d06e1d
-size 8086

 version https://git-lfs.github.com/spec/v1
+oid sha256:f0318e3beae764182399d72dd801a5bba25134842ea2697a20a7865b8c94ad41
+size 8568