Instructions to use EmbeddedLLM/Mistral-7B-Merge-14-v0.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use EmbeddedLLM/Mistral-7B-Merge-14-v0.3 with Transformers:

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

pipe = pipeline("text-generation", model="EmbeddedLLM/Mistral-7B-Merge-14-v0.3")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("EmbeddedLLM/Mistral-7B-Merge-14-v0.3")
model = AutoModelForCausalLM.from_pretrained("EmbeddedLLM/Mistral-7B-Merge-14-v0.3")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use EmbeddedLLM/Mistral-7B-Merge-14-v0.3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "EmbeddedLLM/Mistral-7B-Merge-14-v0.3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "EmbeddedLLM/Mistral-7B-Merge-14-v0.3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.3

SGLang

How to use EmbeddedLLM/Mistral-7B-Merge-14-v0.3 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 "EmbeddedLLM/Mistral-7B-Merge-14-v0.3" \
    --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": "EmbeddedLLM/Mistral-7B-Merge-14-v0.3",
		"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 "EmbeddedLLM/Mistral-7B-Merge-14-v0.3" \
        --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": "EmbeddedLLM/Mistral-7B-Merge-14-v0.3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use EmbeddedLLM/Mistral-7B-Merge-14-v0.3 with Docker Model Runner:
```
docker model run hf.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.3
```

thesunday commited on Jan 21, 2024

Commit

d391d28

verified ·

1 Parent(s): 5fe91ce

Mention v0.4 model ; Add Open LLM Leaderboard scores

Browse files

Files changed (1) hide show

README.md +23 -1

README.md CHANGED Viewed

@@ -21,6 +21,10 @@ base_model:
 - mlabonne/NeuralHermes-2.5-Mistral-7B
 ---
 # Model Description
 This is an update to [EmbeddedLLM/Mistral-7B-Merge-14-v0.2](https://huggingface.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.2) that removes
@@ -52,7 +56,25 @@ The 14 models are as follows:
 - base model: [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
-The yaml config file for this model is here:
 ```yaml
 models:

 - mlabonne/NeuralHermes-2.5-Mistral-7B
 ---
+# Update 2024-01-03
+Check out our [v0.4 model](https://huggingface.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.4) which is based on this and achieves better average score of 71.19 versus 69.66.
 # Model Description
 This is an update to [EmbeddedLLM/Mistral-7B-Merge-14-v0.2](https://huggingface.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.2) that removes
 - base model: [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
+## Open LLM Leaderboard
+|            | v0.3  | v0.4  |
+|------------|-------|-------|
+| Average    | 69.66 | 71.19 |
+| ARC        | 65.96 | 66.81 |
+| HellaSwag  | 85.29 | 86.15 |
+| MMLU       | 64.35 | 65.10 |
+| TruthfulQA | 57.80 | 58.25 |
+| Winogrande | 78.30 | 80.03 |
+| GSM8K      | 66.26 | 70.81 |
+## Chat Template
+We tried ChatML and Llama-2 chat template, but feel free to try other templates.
+## Merge Configuration
+The merge config file for this model is here:
 ```yaml
 models: