Instructions to use prithivMLmods/Novaeus-Promptist-7B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use prithivMLmods/Novaeus-Promptist-7B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="prithivMLmods/Novaeus-Promptist-7B-Instruct")
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("prithivMLmods/Novaeus-Promptist-7B-Instruct")
model = AutoModelForCausalLM.from_pretrained("prithivMLmods/Novaeus-Promptist-7B-Instruct", 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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use prithivMLmods/Novaeus-Promptist-7B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "prithivMLmods/Novaeus-Promptist-7B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prithivMLmods/Novaeus-Promptist-7B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/prithivMLmods/Novaeus-Promptist-7B-Instruct

SGLang

How to use prithivMLmods/Novaeus-Promptist-7B-Instruct 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 "prithivMLmods/Novaeus-Promptist-7B-Instruct" \
    --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": "prithivMLmods/Novaeus-Promptist-7B-Instruct",
		"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 "prithivMLmods/Novaeus-Promptist-7B-Instruct" \
        --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": "prithivMLmods/Novaeus-Promptist-7B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use prithivMLmods/Novaeus-Promptist-7B-Instruct with Docker Model Runner:
```
docker model run hf.co/prithivMLmods/Novaeus-Promptist-7B-Instruct
```

prithivMLmods commited on Dec 6, 2024

Commit

db9b8e8

verified ·

1 Parent(s): ccaecd3

Update README.md

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@@ -20,4 +20,26 @@ tags:
 - Promptist-Instruct
 - text-generation-inference
 - art
 ---

 - Promptist-Instruct
 - text-generation-inference
 - art
+---
+### Novaeus-Promptist-7B-Instruct Uploaded Model Files:
+| **File Name [ Uploaded Files ]**                              | **Size**      | **Description**                          | **Upload Status** |
+|--------------------------------------------|---------------|------------------------------------------|-------------------|
+| `.gitattributes`                           | 1.57 kB       | Git attributes configuration for LFS.    | Uploaded          |
+| `README.md`                                | 400 Bytes     | Documentation about the model.           | Updated           |
+| `added_tokens.json`                        | 657 Bytes     | Custom tokens for tokenizer.             | Uploaded          |
+| `config.json`                              | 860 Bytes     | Configuration for the model.             | Uploaded          |
+| `generation_config.json`                   | 281 Bytes     | Configuration for text generation.       | Uploaded          |
+| `merges.txt`                               | 1.82 MB       | Byte-pair encoding (BPE) merge rules.    | Uploaded          |
+| `pytorch_model-00001-of-00004.bin`         | 4.88 GB       | Model weights (split part 1).            | Uploaded (LFS)    |
+| `pytorch_model-00002-of-00004.bin`         | 4.93 GB       | Model weights (split part 2).            | Uploaded (LFS)    |
+| `pytorch_model-00003-of-00004.bin`         | 4.33 GB       | Model weights (split part 3).            | Uploaded (LFS)    |
+| `pytorch_model-00004-of-00004.bin`         | 1.09 GB       | Model weights (split part 4).            | Uploaded (LFS)    |
+| `pytorch_model.bin.index.json`             | 28.1 kB       | Index file for model weights.            | Uploaded          |
+| `special_tokens_map.json`                  | 644 Bytes     | Map of special tokens for tokenizer.     | Uploaded          |
+| `tokenizer.json`                           | 11.4 MB       | Tokenizer data in JSON format.           | Uploaded (LFS)    |
+| `tokenizer_config.json`                    | 7.73 kB       | Tokenizer configuration file.            | Uploaded          |
+| `vocab.json`                               | 2.78 MB       | Vocabulary for tokenizer.                | Uploaded          |
 ---