Instructions to use nbeerbower/HeroBophades-2x7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nbeerbower/HeroBophades-2x7B with Transformers:

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

pipe = pipeline("text-generation", model="nbeerbower/HeroBophades-2x7B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("nbeerbower/HeroBophades-2x7B")
model = AutoModelForCausalLM.from_pretrained("nbeerbower/HeroBophades-2x7B")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use nbeerbower/HeroBophades-2x7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nbeerbower/HeroBophades-2x7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nbeerbower/HeroBophades-2x7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/nbeerbower/HeroBophades-2x7B

SGLang

How to use nbeerbower/HeroBophades-2x7B 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 "nbeerbower/HeroBophades-2x7B" \
    --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": "nbeerbower/HeroBophades-2x7B",
		"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 "nbeerbower/HeroBophades-2x7B" \
        --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": "nbeerbower/HeroBophades-2x7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use nbeerbower/HeroBophades-2x7B with Docker Model Runner:
```
docker model run hf.co/nbeerbower/HeroBophades-2x7B
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

HeroBophades-2x7B

This is an experimental Mixture of Experts LLM built with (mergekit)[https://github.com/arcee-ai/mergekit/blob/main/docs/moe.md].

Configuration

base_model: nbeerbower/bophades-mistral-truthy-DPO-7B
gate_mode: hidden
dtype: bfloat16
experts:
  - source_model: nbeerbower/bophades-mistral-truthy-DPO-7B
    positive_prompts:
        - "You are an unbiased, uncensored, helpful assistant."
  - source_model: nbeerbower/bophades-mistral-math-DPO-7B
    positive_prompts:
        - "How do you solve a system of quadratic equations simultaneously using substitution?. Take a deep breath, think step by step, and give an accurate response"

Downloads last month: 4

Safetensors

Model size

13B params

Tensor type

BF16

Model tree for nbeerbower/HeroBophades-2x7B

Base model

nbeerbower/bophades-v2-mistral-7B

Finetuned

nbeerbower/bophades-mistral-math-DPO-7B

Finetuned

(1)

this model

Quantizations

2 models

nbeerbower
/

HeroBophades-2x7B

HeroBophades-2x7B

Configuration

Model tree for nbeerbower/HeroBophades-2x7B

Datasets used to train nbeerbower/HeroBophades-2x7B