Instructions to use aiplanet/panda-coder-13B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use aiplanet/panda-coder-13B with Transformers:

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

pipe = pipeline("text-generation", model="aiplanet/panda-coder-13B")
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("aiplanet/panda-coder-13B")
model = AutoModelForCausalLM.from_pretrained("aiplanet/panda-coder-13B", 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 aiplanet/panda-coder-13B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "aiplanet/panda-coder-13B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "aiplanet/panda-coder-13B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/aiplanet/panda-coder-13B

SGLang

How to use aiplanet/panda-coder-13B 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 "aiplanet/panda-coder-13B" \
    --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": "aiplanet/panda-coder-13B",
		"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 "aiplanet/panda-coder-13B" \
        --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": "aiplanet/panda-coder-13B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use aiplanet/panda-coder-13B with Docker Model Runner:
```
docker model run hf.co/aiplanet/panda-coder-13B
```

lucifertrj commited on Dec 6, 2023

Commit

0cb5dd1

1 Parent(s): 3a263de

add citation

Browse files

Files changed (1) hide show

README.md +14 -20

README.md CHANGED Viewed

@@ -41,29 +41,23 @@ You can schedule 1:1 meeting with our DevRel & Community Team to get started wit
 Stay tuned for more updates and be a part of the coding evolution. Join us on this exciting journey as we make AI accessible to all at AI Planet!
-## Training and evaluation data
-More information needed
-## Training procedure
-### Training hyperparameters
-The following hyperparameters were used during training:
-- learning_rate: 0.001
-- train_batch_size: 1
-- eval_batch_size: 8
-- seed: 42
-- gradient_accumulation_steps: 8
-- total_train_batch_size: 8
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: constant
-- lr_scheduler_warmup_ratio: 0.03
-- training_steps: 512
 ### Framework versions
 - Transformers 4.33.3
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.5
 - Tokenizers 0.13.3

 Stay tuned for more updates and be a part of the coding evolution. Join us on this exciting journey as we make AI accessible to all at AI Planet!
 ### Framework versions
 - Transformers 4.33.3
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.5
 - Tokenizers 0.13.3
+```
+### Citation
+```
+@misc {lucifertrj,
+	author       = { {Tarun Jain} },
+	title        = { Panda Coder-13B by AI Planet},
+	year         = 2023,
+	url          = { https://huggingface.co/aiplanet/panda-coder-13B },
+	publisher    = { Hugging Face }
+}
+```