Instructions to use sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0 with Transformers:

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

pipe = pipeline("text-generation", model="sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0")
model = AutoModelForCausalLM.from_pretrained("sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0

SGLang

How to use sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0 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 "sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0" \
    --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": "sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0",
		"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 "sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0" \
        --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": "sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0 with Docker Model Runner:
```
docker model run hf.co/sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

wizard-tulu-dolphin-70b-v1.0-slerp

I used this blend as part of Midnight Rose v2.0.3. I haven't tested it much on its own, but I created this blend to be good at instruction following. It's nothing fancy. I just figured that WizardLM, Tulu, and Dolphin 2.2 together would be a heavy hitter for smarts.

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

/home/llm/mergequant/models/BASE/ehartford_dolphin-2.2-70b-32000vocab
/home/llm/mergequant/models/wizard-tulu-70b-v1.0

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: /home/llm/mergequant/models/wizard-tulu-70b-v1.0
  - model: /home/llm/mergequant/models/BASE/ehartford_dolphin-2.2-70b-32000vocab
merge_method: slerp
base_model: /home/llm/mergequant/models/wizard-tulu-70b-v1.0
parameters:
  t:
    - value: 0.5
dtype: float16

models:
  - model: /home/llm/mergequant/models/BASE/NousResearch_Llama-2-70b-hf
    # no parameters necessary for base model
  - model: /home/llm/mergequant/models/BASE/allenai_tulu-2-dpo-70b
    parameters:
      density: 0.35
      weight: 0.75
  - model: /home/llm/mergequant/models/BASE/WizardLM_WizardLM-70B-V1.0
    parameters:
      density: 0.35
      weight: 0.5
merge_method: dare_ties
base_model: /home/llm/mergequant/models/BASE/NousResearch_Llama-2-70b-hf
parameters:
  normalize: true
  int8_mask: true
dtype: float16
tokenzer_source: union

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Safetensors

Model size

69B params

Tensor type

F16

Model tree for sophosympatheia/Wizard-Tulu-Dolphin-70B-v1.0

Quantizations

2 models