Instructions to use neongeckocom/NeonLLM-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use neongeckocom/NeonLLM-Base with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("neongeckocom/NeonLLM-Base")
model = AutoModelForCausalLM.from_pretrained("neongeckocom/NeonLLM-Base")
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 neongeckocom/NeonLLM-Base with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/neongeckocom/NeonLLM-Base

SGLang

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

Docker Model Runner
How to use neongeckocom/NeonLLM-Base with Docker Model Runner:
```
docker model run hf.co/neongeckocom/NeonLLM-Base
```

NeonBohdan commited on Jun 27, 2024

Commit

75b86f7

1 Parent(s): 6b8ad37

Max seq len = 8192

Browse files

Files changed (2) hide show

config.json +1 -1
tokenizer_config.json +1 -1

config.json CHANGED Viewed

@@ -10,7 +10,7 @@
   "hidden_size": 4096,
   "initializer_range": 0.02,
   "intermediate_size": 14336,
-  "max_position_embeddings": 32768,
   "model_type": "mistral",
   "num_attention_heads": 32,
   "num_hidden_layers": 32,

   "hidden_size": 4096,
   "initializer_range": 0.02,
   "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
   "model_type": "mistral",
   "num_attention_heads": 32,
   "num_hidden_layers": 32,

tokenizer_config.json CHANGED Viewed

@@ -290,7 +290,7 @@
   "clean_up_tokenization_spaces": true,
   "eos_token": "<|im_end|>",
   "legacy": true,
-  "model_max_length": 1000000000000000019884624838656,
   "pad_token": "</s>",
   "sp_model_kwargs": {},
   "spaces_between_special_tokens": false,

   "clean_up_tokenization_spaces": true,
   "eos_token": "<|im_end|>",
   "legacy": true,
+  "model_max_length": 8192,
   "pad_token": "</s>",
   "sp_model_kwargs": {},
   "spaces_between_special_tokens": false,