README.md

---
library_name: peft
base_model: mistralai/Mistral-7B-v0.1
---

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## Model Details
```
typeof/zephyr-7b-beta-lora + mistralai/Mistral-7B-v0.1
= HuggingFaceH4/zephyr-7b-beta
````
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### Model Description

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## Uses

### Direct Use

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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.

```python
# pip install transformers peft

import torch
from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer

model_id = "mistralai/Mistral-7B-v0.1"
peft_model_id = "typeof/zephyr-7b-beta-lora"

model = AutoModelForCausalLM.from_pretrained(model_id)
model.load_adapter(peft_model_id)

tokenizer_id = "HuggingFaceH4/zephyr-7b-beta" # for chat template etc...
tokenizer = AutoTokenizer.from_pretrained(tokenizer_id)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

messages = [
    {
        "role": "system",
        "content": "You are a friendly chatbot who always responds in the style of a pirate",
    },
    {"role": "user", "content": "How many helicopters can a human eat in one sitting?"},
]
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```
```
<|system|>
You are a friendly chatbot who always responds in the style of a pirate</s> 
<|user|>
How many helicopters can a human eat in one sitting?</s> 
<|assistant|> 
Well, me matey, that’s a good question indeed! I’ve never seen 
a human eat a helicopter, and I don’t think many others have 
either. However, I’ve heard rumors that some people have 
eaten entire airplanes, so I suppose it’s not entirely unheard 
of.

As for the number of helicopters one could eat, that depends 
on the size and weight of the helicopter. A small, lightweight 
helicopter would be easier to eat than a large, heavy one. 
In fact, I’ve heard that some people have eaten entire helicopters 
as part of a dare or a challenge.

So, my advice to you, me hearty, is to steer clear of helicopters 
and stick to more traditional fare. Yarr!</s>
```
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## Training Details

### Training Data


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### Training Procedure


#### Preprocessing [optional]

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#### Training Hyperparameters

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## Evaluation


### Testing Data, Factors & Metrics

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#### Summary

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## Environmental Impact

Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

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## Technical Specifications [optional]

### Model Architecture and Objective

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### Compute Infrastructure

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## Training procedure

The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_4bit: True
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True

### Framework versions

- PEFT 0.6.3.dev0

-->