Instructions to use notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw with Transformers:

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

pipe = pipeline("text-generation", model="notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw")
model = AutoModelForCausalLM.from_pretrained("notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw

SGLang

How to use notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw 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 "notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw" \
    --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": "notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw",
		"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 "notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw" \
        --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": "notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw with Docker Model Runner:
```
docker model run hf.co/notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw
```

Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw

This is a merge of pre-trained language models created using mergekit.

Merge Details

An experimental merge.

Prompt format: ChatML or Mixtral-8x7B-Instruct-v0.1

Merge Method

This model was merged using the DARE TIES merge method using ./models/Mixtral-8x7B-v0.1 as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: ./models/Mixtral-8x7B-Instruct-v0.1
    parameters:
      density: 0.5
      weight: 1.0
  - model: ./models/Nous-Hermes-2-Mixtral-8x7B-DPO
    parameters:
      density: 0.5
      weight: 0.5
merge_method: dare_ties
base_model: ./models/Mixtral-8x7B-v0.1
parameters:
  #normalize: false
  #int8_mask: true
dtype: bfloat16

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Papers for notstoic/Nous-Hermes-2-Mixtruct-v0.1-8x7B-DPO-DARE_TIES-exl2-5.0bpw

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