Instructions to use AlignmentLab-AI/teensyorca with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AlignmentLab-AI/teensyorca with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AlignmentLab-AI/teensyorca")
model = AutoModelForCausalLM.from_pretrained("AlignmentLab-AI/teensyorca")
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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use AlignmentLab-AI/teensyorca with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/AlignmentLab-AI/teensyorca

SGLang

How to use AlignmentLab-AI/teensyorca 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 "AlignmentLab-AI/teensyorca" \
    --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": "AlignmentLab-AI/teensyorca",
		"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 "AlignmentLab-AI/teensyorca" \
        --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": "AlignmentLab-AI/teensyorca",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use AlignmentLab-AI/teensyorca with Docker Model Runner:
```
docker model run hf.co/AlignmentLab-AI/teensyorca
```

Alignment-Lab-AI commited on Jan 13, 2024

Commit

70dfb55

verified ·

1 Parent(s): 766f49d

Upload 3 files

Browse files

Files changed (3) hide show

adapter_config.json +28 -0
adapter_model.bin +3 -0
tokenizer_config.json +5 -2

adapter_config.json ADDED Viewed

	@@ -0,0 +1,28 @@

+{
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+  "base_model_name_or_path": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
+  "bias": "none",
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+  "inference_mode": true,
+  "init_lora_weights": true,
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+  "lora_dropout": 0,
+  "modules_to_save": null,
+  "peft_type": "LORA",
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+  "task_type": "CAUSAL_LM"
+}

adapter_model.bin ADDED Viewed

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

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+size 50569181

tokenizer_config.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
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       "content": "<unk>",
@@ -36,7 +36,10 @@
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   "padding_side": "right",
   "sp_model_kwargs": {},
   "tokenizer_class": "LlamaTokenizer",
   "unk_token": "<unk>",
-  "use_default_system_prompt": false
 }

 {
   "add_bos_token": true,
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   "added_tokens_decoder": {
     "0": {
       "content": "<unk>",
   "pad_token": "</s>",
   "padding_side": "right",
   "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
   "tokenizer_class": "LlamaTokenizer",
+  "trust_remote_code": false,
   "unk_token": "<unk>",
+  "use_default_system_prompt": false,
+  "use_fast": true
 }