Instructions to use ChaoticNeutrals/BuRP_7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ChaoticNeutrals/BuRP_7B with Transformers:

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

pipe = pipeline("text-generation", model="ChaoticNeutrals/BuRP_7B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ChaoticNeutrals/BuRP_7B")
model = AutoModelForCausalLM.from_pretrained("ChaoticNeutrals/BuRP_7B")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use ChaoticNeutrals/BuRP_7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ChaoticNeutrals/BuRP_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/BuRP_7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ChaoticNeutrals/BuRP_7B

SGLang

How to use ChaoticNeutrals/BuRP_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/BuRP_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/BuRP_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/BuRP_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/BuRP_7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ChaoticNeutrals/BuRP_7B with Docker Model Runner:
```
docker model run hf.co/ChaoticNeutrals/BuRP_7B
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

BuRP

So you want a model that can do it all? You've been dying to RP with a superintelligence who never refuses your advances while sticking to your strange and oddly specific dialogue format?

Well, look no further because BuRP is the model you need.

GGUF quants here: https://huggingface.co/Lewdiculous/BuRP_7B-GGUF-IQ-Imatrix

GPTQ quant here: https://huggingface.co/Test157t/ChaoticNeutrals-BuRP_7B-GPTQ

Configuration

The following YAML configuration was used to produce this model:

slices:
  - sources:
      - model: ErisLaylaSLERP
        layer_range: [0, 32]
      - model: ParadigmInfinitySLERP
        layer_range: [0, 32]
merge_method: slerp
base_model: ParadigmInfinitySLERP
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

Downloads last month: 10

Safetensors

Model size

7B params

Tensor type

BF16

Model tree for ChaoticNeutrals/BuRP_7B

Merges

11 models

Quantizations

2 models

ChaoticNeutrals
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BuRP_7B

BuRP

Configuration

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