Instructions to use clgptcapstone/ft-rectangle-class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use clgptcapstone/ft-rectangle-class with Transformers:

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

pipe = pipeline("text-generation", model="clgptcapstone/ft-rectangle-class")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("clgptcapstone/ft-rectangle-class")
model = AutoModelForCausalLM.from_pretrained("clgptcapstone/ft-rectangle-class")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use clgptcapstone/ft-rectangle-class with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/clgptcapstone/ft-rectangle-class

SGLang

How to use clgptcapstone/ft-rectangle-class 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 "clgptcapstone/ft-rectangle-class" \
    --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": "clgptcapstone/ft-rectangle-class",
		"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 "clgptcapstone/ft-rectangle-class" \
        --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": "clgptcapstone/ft-rectangle-class",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use clgptcapstone/ft-rectangle-class with Docker Model Runner:
```
docker model run hf.co/clgptcapstone/ft-rectangle-class
```

jonathan1999 commited on Jun 24, 2024

Commit

6f65dbe

verified ·

1 Parent(s): ab5b0b2

Upload tokenizer

Browse files

Files changed (1) hide show

special_tokens_map.json +7 -1

special_tokens_map.json CHANGED Viewed

@@ -13,7 +13,13 @@
     "rstrip": false,
     "single_word": false
   },
-  "pad_token": "<|endoftext|>",
   "unk_token": {
     "content": "<|endoftext|>",
     "lstrip": false,

     "rstrip": false,
     "single_word": false
   },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
   "unk_token": {
     "content": "<|endoftext|>",
     "lstrip": false,