Instructions to use NECOUDBFM/Jellyfish-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NECOUDBFM/Jellyfish-8B with Transformers:

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

pipe = pipeline("text-generation", model="NECOUDBFM/Jellyfish-8B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("NECOUDBFM/Jellyfish-8B")
model = AutoModelForCausalLM.from_pretrained("NECOUDBFM/Jellyfish-8B", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use NECOUDBFM/Jellyfish-8B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "NECOUDBFM/Jellyfish-8B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "NECOUDBFM/Jellyfish-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/NECOUDBFM/Jellyfish-8B

SGLang

How to use NECOUDBFM/Jellyfish-8B 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 "NECOUDBFM/Jellyfish-8B" \
    --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": "NECOUDBFM/Jellyfish-8B",
		"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 "NECOUDBFM/Jellyfish-8B" \
        --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": "NECOUDBFM/Jellyfish-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use NECOUDBFM/Jellyfish-8B with Docker Model Runner:
```
docker model run hf.co/NECOUDBFM/Jellyfish-8B
```

yuyangdong commited on Apr 23, 2024

Commit

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@@ -59,8 +59,8 @@ If you find our work useful, please give us credit by citing:
 | Data Imputation  | Unseen |  Phone       | 86.70| -- | 90.79 | 87.21 | 85.00|  86.93 |
 | Error Detection  | Seen |  Hosptial      | 94.40| 90.74 | 90.74 | 95.59 | 96.27 |  93.66|
 | Error Detection  | Seen |  Adult         | 99.10| 92.01 | 92.01 | 99.33 | 91.96 |  92.98|
-| Error Detection  | Unseen |  Flights     | 81.00 | -- | 83.48  | 82.52 | 66.92 |
-| Error Detection  | Unseen |  Rayyan      | 79.00| -- | 81.95 | 90.65 | 69.82 |
 | Schema Matching  | Seen |  Sythea        | 38.50| 57.14 | 66.67 | 36.36 | 44.44 | 40.00 |
 | Schema Matching  | Seen |  MIMIC        | 20.00| -- | 40.00 | 40.00 | 40.00 | 40.82|
 | Schema Matching  | Unseen |  CMS        | 50.00| -- | 19.35 | 59.29 | 13.79 |  68.49|

 | Data Imputation  | Unseen |  Phone       | 86.70| -- | 90.79 | 87.21 | 85.00|  86.93 |
 | Error Detection  | Seen |  Hosptial      | 94.40| 90.74 | 90.74 | 95.59 | 96.27 |  93.66|
 | Error Detection  | Seen |  Adult         | 99.10| 92.01 | 92.01 | 99.33 | 91.96 |  92.98|
+| Error Detection  | Unseen |  Flights     | 81.00 | -- | 83.48  | 82.52 | 66.92 | 82.33 |
+| Error Detection  | Unseen |  Rayyan      | 79.00| -- | 81.95 | 90.65 | 69.82 | 98.31 |
 | Schema Matching  | Seen |  Sythea        | 38.50| 57.14 | 66.67 | 36.36 | 44.44 | 40.00 |
 | Schema Matching  | Seen |  MIMIC        | 20.00| -- | 40.00 | 40.00 | 40.00 | 40.82|
 | Schema Matching  | Unseen |  CMS        | 50.00| -- | 19.35 | 59.29 | 13.79 |  68.49|