Instructions to use RUCKBReasoning/TableLLM-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use RUCKBReasoning/TableLLM-7b with Transformers:

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

pipe = pipeline("text-generation", model="RUCKBReasoning/TableLLM-7b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("RUCKBReasoning/TableLLM-7b")
model = AutoModelForCausalLM.from_pretrained("RUCKBReasoning/TableLLM-7b")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use RUCKBReasoning/TableLLM-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "RUCKBReasoning/TableLLM-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RUCKBReasoning/TableLLM-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/RUCKBReasoning/TableLLM-7b

SGLang

How to use RUCKBReasoning/TableLLM-7b 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 "RUCKBReasoning/TableLLM-7b" \
    --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": "RUCKBReasoning/TableLLM-7b",
		"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 "RUCKBReasoning/TableLLM-7b" \
        --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": "RUCKBReasoning/TableLLM-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use RUCKBReasoning/TableLLM-7b with Docker Model Runner:
```
docker model run hf.co/RUCKBReasoning/TableLLM-7b
```

KAKA22 commited on Jul 31, 2024

Commit

f2b3853

verified ·

1 Parent(s): 45004d3

Upload tokenizer.json with huggingface_hub

Browse files

Files changed (1) hide show

tokenizer.json +0 -36

tokenizer.json CHANGED Viewed

@@ -34,42 +34,6 @@
       "rstrip": false,
       "normalized": false,
       "special": true
-    },
-    {
-      "id": 32007,
-      "content": "▁<PRE>",
-      "single_word": false,
-      "lstrip": false,
-      "rstrip": false,
-      "normalized": false,
-      "special": true
-    },
-    {
-      "id": 32008,
-      "content": "▁<SUF>",
-      "single_word": false,
-      "lstrip": false,
-      "rstrip": false,
-      "normalized": false,
-      "special": true
-    },
-    {
-      "id": 32009,
-      "content": "▁<MID>",
-      "single_word": false,
-      "lstrip": false,
-      "rstrip": false,
-      "normalized": false,
-      "special": true
-    },
-    {
-      "id": 32010,
-      "content": "▁<EOT>",
-      "single_word": false,
-      "lstrip": false,
-      "rstrip": false,
-      "normalized": false,
-      "special": true
     }
   ],
   "normalizer": {

       "rstrip": false,
       "normalized": false,
       "special": true
     }
   ],
   "normalizer": {