Instructions to use ChaoticNeutrals/Prima-LelantaclesV5-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ChaoticNeutrals/Prima-LelantaclesV5-7b with Transformers:

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

pipe = pipeline("text-generation", model="ChaoticNeutrals/Prima-LelantaclesV5-7b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ChaoticNeutrals/Prima-LelantaclesV5-7b")
model = AutoModelForCausalLM.from_pretrained("ChaoticNeutrals/Prima-LelantaclesV5-7b", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ChaoticNeutrals/Prima-LelantaclesV5-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ChaoticNeutrals/Prima-LelantaclesV5-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ChaoticNeutrals/Prima-LelantaclesV5-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ChaoticNeutrals/Prima-LelantaclesV5-7b

SGLang

How to use ChaoticNeutrals/Prima-LelantaclesV5-7b 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 "ChaoticNeutrals/Prima-LelantaclesV5-7b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ChaoticNeutrals/Prima-LelantaclesV5-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "ChaoticNeutrals/Prima-LelantaclesV5-7b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ChaoticNeutrals/Prima-LelantaclesV5-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ChaoticNeutrals/Prima-LelantaclesV5-7b with Docker Model Runner:
```
docker model run hf.co/ChaoticNeutrals/Prima-LelantaclesV5-7b
```

Prima-LelantaclesV5-7b

File size: 1,080 Bytes

---
base_model:
- Test157t/Pasta-Lake-7b
- Test157t/Prima-LelantaclesV4-7b-16k
library_name: transformers
tags:
- mergekit
- merge
license: other
---

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/642265bc01c62c1e4102dc36/_AugGaelWylUuIIDmYOXG.jpeg)

https://huggingface.co/ChaoticNeutrals/Prima-LelantaclesV5-7b/tree/main/ST%20presets

This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method.

The following models were included in the merge:
* [Test157t/Pasta-Lake-7b](https://huggingface.co/Test157t/Pasta-Lake-7b) +  [Test157t/Prima-LelantaclesV4-7b-16k](https://huggingface.co/Test157t/Prima-LelantaclesV4-7b-16k)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
merge_method: dare_ties
base_model: Test157t/Prima-LelantaclesV4-7b-16k
parameters:
  normalize: true
models:
  - model: Test157t/Pasta-Lake-7b
    parameters:
      weight: 1
  - model: Test157t/Prima-LelantaclesV4-7b-16k
    parameters:
      weight: 1
dtype: float16

```