Instructions to use HuggingFaceH4/zephyr-7b-beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use HuggingFaceH4/zephyr-7b-beta with Transformers:

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

pipe = pipeline("text-generation", model="HuggingFaceH4/zephyr-7b-beta")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("HuggingFaceH4/zephyr-7b-beta")
model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/zephyr-7b-beta", 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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use HuggingFaceH4/zephyr-7b-beta with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "HuggingFaceH4/zephyr-7b-beta"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HuggingFaceH4/zephyr-7b-beta",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/HuggingFaceH4/zephyr-7b-beta

SGLang

How to use HuggingFaceH4/zephyr-7b-beta 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 "HuggingFaceH4/zephyr-7b-beta" \
    --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": "HuggingFaceH4/zephyr-7b-beta",
		"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 "HuggingFaceH4/zephyr-7b-beta" \
        --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": "HuggingFaceH4/zephyr-7b-beta",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use HuggingFaceH4/zephyr-7b-beta with Docker Model Runner:
```
docker model run hf.co/HuggingFaceH4/zephyr-7b-beta
```

Wauplin HF Staff commited on Nov 29, 2023

Commit

a14ed68

1 Parent(s): 6581330

Update README.md

Browse files

Files changed (1) hide show

README.md +12 -7

README.md CHANGED Viewed

@@ -16,8 +16,7 @@ pipeline_tag: text-generation
 model-index:
 - name: zephyr-7b-beta
   results:
-  # AI2 Reasoning Challenge (25-Shot) (Open LLM Leaderboard)
   - task:
       type: text-generation
       name: Text Generation
@@ -43,7 +42,7 @@ model-index:
       name: Open LLM Leaderboard
       url: https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-beta_public
-  # HellaSwag (10-shot) (Open LLM Leaderboard)
   - task:
       type: text-generation
       name: Text Generation
@@ -68,7 +67,7 @@ model-index:
       name: Open LLM Leaderboard
       url: https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-beta_public
-  # DROP (3-shot) (Open LLM Leaderboard)
   - task:
       type: text-generation
       name: Text Generation
@@ -93,7 +92,7 @@ model-index:
       name: Open LLM Leaderboard
       url: https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-beta_public
-  # TruthfulQA (0-shot) (Open LLM Leaderboard)
   - task:
       type: text-generation
       name: Text Generation
@@ -117,7 +116,7 @@ model-index:
       name: Open LLM Leaderboard
       url: https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-beta_public
-  # GSM8k (5-shot) (Open LLM Leaderboard)
   - task:
       type: text-generation
       name: Text Generation
@@ -137,7 +136,7 @@ model-index:
       name: Open LLM Leaderboard
       url: https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-beta_public
-  # MMLU (5-Shot) (Open LLM Leaderboard)
   # ???
   # AlpacaEval (taken from model card)
@@ -296,7 +295,9 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 3.0
 ### Training results
 The table below shows the full set of DPO training metrics:
 | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
 |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
@@ -358,12 +359,16 @@ The table below shows the full set of DPO training metrics:
 | 0.0077        | 2.89  | 5600 | 0.7520          | -4.5586        | -8.3485          | 0.7969             | 3.7899          | -340.4545      | -299.8206    | -2.3078         | -2.3517       |
 | 0.0094        | 2.94  | 5700 | 0.7527          | -4.5542        | -8.3509          | 0.7812             | 3.7967          | -340.4790      | -299.7773    | -2.3062         | -2.3510       |
 | 0.0054        | 2.99  | 5800 | 0.7520          | -4.5169        | -8.3079          | 0.7812             | 3.7911          | -340.0493      | -299.4038    | -2.3081         | -2.3530       |
 ### Framework versions
 - Transformers 4.35.0.dev0
 - Pytorch 2.0.1+cu118
 - Datasets 2.12.0
 - Tokenizers 0.14.0
 ## Citation
 If you find Zephyr-7B-β is useful in your work, please cite it with:
 ```
 @misc{tunstall2023zephyr,

 model-index:
 - name: zephyr-7b-beta
   results:
+  # AI2 Reasoning Challenge (25-Shot)
   - task:
       type: text-generation
       name: Text Generation
       name: Open LLM Leaderboard
       url: https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-beta_public
+  # HellaSwag (10-shot)
   - task:
       type: text-generation
       name: Text Generation
       name: Open LLM Leaderboard
       url: https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-beta_public
+  # DROP (3-shot)
   - task:
       type: text-generation
       name: Text Generation
       name: Open LLM Leaderboard
       url: https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-beta_public
+  # TruthfulQA (0-shot)
   - task:
       type: text-generation
       name: Text Generation
       name: Open LLM Leaderboard
       url: https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-beta_public
+  # GSM8k (5-shot)
   - task:
       type: text-generation
       name: Text Generation
       name: Open LLM Leaderboard
       url: https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-beta_public
+  # MMLU (5-Shot)
   # ???
   # AlpacaEval (taken from model card)
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 3.0
 ### Training results
 The table below shows the full set of DPO training metrics:
 | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
 |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
 | 0.0077        | 2.89  | 5600 | 0.7520          | -4.5586        | -8.3485          | 0.7969             | 3.7899          | -340.4545      | -299.8206    | -2.3078         | -2.3517       |
 | 0.0094        | 2.94  | 5700 | 0.7527          | -4.5542        | -8.3509          | 0.7812             | 3.7967          | -340.4790      | -299.7773    | -2.3062         | -2.3510       |
 | 0.0054        | 2.99  | 5800 | 0.7520          | -4.5169        | -8.3079          | 0.7812             | 3.7911          | -340.0493      | -299.4038    | -2.3081         | -2.3530       |
 ### Framework versions
 - Transformers 4.35.0.dev0
 - Pytorch 2.0.1+cu118
 - Datasets 2.12.0
 - Tokenizers 0.14.0
 ## Citation
 If you find Zephyr-7B-β is useful in your work, please cite it with:
 ```
 @misc{tunstall2023zephyr,