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---
library_name: peft
base_model: mistralai/Mistral-7B-v0.1
language:
- en
tags:
- Δ
- LoRA
---
<!--
# Model Card for Model ID
-->
## Model Details
<!--![image/png](https://cdn-uploads.huggingface.co/production/uploads/648b0f4fd8fe693f51de98d2/aerBANxBtCya732NdBiw0.png)-->
$$
W_{mistral} + LoRA_{hermes} = W_{hermes} \\
W_{hermes} - LoRA_{hermes} = W_{mistral}
$$
### Why Though?
unfortunately this is not as simple as [typeof/zephyr-7b-beta-lora](https://huggingface.co/typeof/zephyr-7b-beta-lora)
due to the way in which [OpenHermes](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) was trained...
by adding tokens, the corresponance is not 1-to-1 with [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
as is the case with [typeof/zephyr-7b-beta-lora](https://huggingface.co/typeof/zephyr-7b-beta-lora) ...
nevertheless, if you have found yourself here, I'm sure you can figure out how to use it... if not, open up an issue!
<!--
$$ W_{mistral} + LoRA_{zephyr} = W_{zephyr} $$
```
typeof/zephyr-7b-beta-lora + mistralai/Mistral-7B-v0.1
= HuggingFaceH4/zephyr-7b-beta
````
### Model Description
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
### Direct Use
[More Information Needed]
### Downstream Use [optional]
[More Information Needed]
### Out-of-Scope Use
[More Information Needed]
## Bias, Risks, and Limitations
[More Information Needed]
### 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.
[More Information Needed]
<!--
```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>
```
-->
#### Summary
A fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
[LoRA](https://arxiv.org/abs/2305.14314)
[QLoRA](https://arxiv.org/abs/2106.09685)