Not-For-All-Audiences

Instructions to use Lexic0n/Mistral_7B-Open_Hermes-NSFWV1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Lexic0n/Mistral_7B-Open_Hermes-NSFWV1 with Transformers:

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

pipe = pipeline("text-generation", model="Lexic0n/Mistral_7B-Open_Hermes-NSFWV1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Lexic0n/Mistral_7B-Open_Hermes-NSFWV1")
model = AutoModelForCausalLM.from_pretrained("Lexic0n/Mistral_7B-Open_Hermes-NSFWV1", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Lexic0n/Mistral_7B-Open_Hermes-NSFWV1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Lexic0n/Mistral_7B-Open_Hermes-NSFWV1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Lexic0n/Mistral_7B-Open_Hermes-NSFWV1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Lexic0n/Mistral_7B-Open_Hermes-NSFWV1

SGLang

How to use Lexic0n/Mistral_7B-Open_Hermes-NSFWV1 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 "Lexic0n/Mistral_7B-Open_Hermes-NSFWV1" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Lexic0n/Mistral_7B-Open_Hermes-NSFWV1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "Lexic0n/Mistral_7B-Open_Hermes-NSFWV1" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Lexic0n/Mistral_7B-Open_Hermes-NSFWV1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Lexic0n/Mistral_7B-Open_Hermes-NSFWV1 with Docker Model Runner:
```
docker model run hf.co/Lexic0n/Mistral_7B-Open_Hermes-NSFWV1
```

Lexic0n commited on Apr 7, 2024

Commit

8430365

verified ·

1 Parent(s): cf8a2cd

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@@ -1,3 +1,83 @@
 ---
 license: apache-2.0
 ---

 ---
 license: apache-2.0
+language:
+- en
+tags:
+- not-for-all-audiences
 ---
+# Model Card for Mistral_7B-Open_Hermes-NSFWV1
+<!-- Provide a quick summary of what the model is/does. -->
+This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
+## Model Details
+### Model Description
+This is a fine-tuned version of teknium/OpenHermes-2p5-Mistral-7B,
+- **Model type:** Mistral
+- **Language(s) (NLP):** English
+- **License:** apache-2.0
+- **Finetuned from model :** teknium/OpenHermes-2p5-Mistral-7B
+### Model Sources [optional]
+<!-- Provide the basic links for the model. -->
+- **Repository:** * [teknium/OpenHermes-2p5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)
+## Uses
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+### Direct Use
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+[More Information Needed]
+### Downstream Use [optional]
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+[More Information Needed]
+### Out-of-Scope Use
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+[More Information Needed]
+## Bias, Risks, and Limitations
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+[More Information Needed]
+### Recommendations
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+## How to Get Started with the Model
+Use the code below to get started with the model.
+[More Information Needed]
+## Training Details
+### Training Data
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+[More Information Needed]
+### Training Procedure
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->