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

Libraries

How to use wooldover/pygbot with Transformers:

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

pipe = pipeline("text-generation", model="wooldover/pygbot")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("wooldover/pygbot")
model = AutoModelForCausalLM.from_pretrained("wooldover/pygbot")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use wooldover/pygbot with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "wooldover/pygbot"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "wooldover/pygbot",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/wooldover/pygbot

SGLang

How to use wooldover/pygbot 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 "wooldover/pygbot" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "wooldover/pygbot",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "wooldover/pygbot" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "wooldover/pygbot",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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

wooldover
/

pygbot

Upload 12 files

+version https://git-lfs.github.com/spec/v1
+oid sha256:e86f260301898cfb5a103d722cf81fd38ea2867a81872edaa14cb80d0c653222
+size 38040

+version https://git-lfs.github.com/spec/v1
+oid sha256:c0a0acd1b8418ff56b1c534a1de32b482f86f3b1d3f6f34b0dc22a62640814c9
+size 8780

+version https://git-lfs.github.com/spec/v1
+oid sha256:40304872df2bb5cb1949b860be7fe1939a1a1f6da8c4128844addb9614fffa04
+size 25120

+version https://git-lfs.github.com/spec/v1
+oid sha256:13a83d8a1c87d9e2cc8c779c5dd3487f2a4370af36cd9782fcd9caa0b544fd54
+size 348225

+version https://git-lfs.github.com/spec/v1
+oid sha256:e435102a9fc72734f34812d557d4fde62b6b08e33016c3546144ba9e9d20ce72
+size 10876

+version https://git-lfs.github.com/spec/v1
+oid sha256:7206a92a45e26574516bfbb4753cb390371d70ae6d3689c858623eab0b9073a8
+size 207085

+version https://git-lfs.github.com/spec/v1
+oid sha256:de8491a736621bcaef912ff81e117bbcbfbdc4e92539fcf5a00d65bbf732a9ae
+size 3523

+version https://git-lfs.github.com/spec/v1
+oid sha256:c0482fcdb60b74e238562d889ebb553060d2b192206cf447cd02a5f3588dadbe
+size 2362

+version https://git-lfs.github.com/spec/v1
+oid sha256:646342d34ac20fc8a7c4673df7adfe64b125579a04ddb4389e43e2f41b9fc26f
+size 1655626

+version https://git-lfs.github.com/spec/v1
+oid sha256:e3c8f82eb3e18090483a2cb6b4ed6f8bfa03af1298c05b8db403c2d9739d0183
+size 8554

	@@ -0,0 +1,3 @@

	@@ -0,0 +1,3 @@

	@@ -0,0 +1,3 @@

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:cc4aeb4e3f0fea0093b23ac917e6edad9559233831bc25291f72ee85d3909ce5
+size 2196537