Instructions to use PipableAI/pip-api-data-training-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use PipableAI/pip-api-data-training-v1 with Transformers:

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

pipe = pipeline("text-generation", model="PipableAI/pip-api-data-training-v1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("PipableAI/pip-api-data-training-v1")
model = AutoModelForCausalLM.from_pretrained("PipableAI/pip-api-data-training-v1")
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 PipableAI/pip-api-data-training-v1 with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/PipableAI/pip-api-data-training-v1

SGLang

How to use PipableAI/pip-api-data-training-v1 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 "PipableAI/pip-api-data-training-v1" \
    --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": "PipableAI/pip-api-data-training-v1",
		"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 "PipableAI/pip-api-data-training-v1" \
        --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": "PipableAI/pip-api-data-training-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use PipableAI/pip-api-data-training-v1 with Docker Model Runner:
```
docker model run hf.co/PipableAI/pip-api-data-training-v1
```

QagentS commited on May 24, 2024

Commit

3431664

verified ·

1 Parent(s): 867af48

Upload LlamaForCausalLM

Browse files

Files changed (3) hide show

config.json +3 -2
generation_config.json +1 -1
model.safetensors +1 -1

config.json CHANGED Viewed

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "PipableAI/pip-code-bandit-v1",
   "architectures": [
     "LlamaForCausalLM"
   ],
@@ -12,6 +12,7 @@
   "initializer_range": 0.02,
   "intermediate_size": 5504,
   "max_position_embeddings": 16384,
   "model_type": "llama",
   "num_attention_heads": 16,
   "num_hidden_layers": 24,
@@ -25,7 +26,7 @@
   "rope_theta": 100000,
   "tie_word_embeddings": false,
   "torch_dtype": "bfloat16",
-  "transformers_version": "4.40.2",
   "use_cache": true,
   "vocab_size": 32256
 }

 {
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   "architectures": [
     "LlamaForCausalLM"
   ],
   "initializer_range": 0.02,
   "intermediate_size": 5504,
   "max_position_embeddings": 16384,
+  "mlp_bias": false,
   "model_type": "llama",
   "num_attention_heads": 16,
   "num_hidden_layers": 24,
   "rope_theta": 100000,
   "tie_word_embeddings": false,
   "torch_dtype": "bfloat16",
+  "transformers_version": "4.41.0",
   "use_cache": true,
   "vocab_size": 32256
 }

generation_config.json CHANGED Viewed

@@ -2,5 +2,5 @@
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   "bos_token_id": 32013,
   "eos_token_id": 32021,
-  "transformers_version": "4.40.2"
 }

   "_from_model_config": true,
   "bos_token_id": 32013,
   "eos_token_id": 32021,
+  "transformers_version": "4.41.0"
 }

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