Text Generation
Transformers
Safetensors
mistral
Safetensors
text-generation-inference
Merge
7b
mistralai/Mistral-7B-Instruct-v0.1
chargoddard/loyal-piano-m7
en
dataset:pankajmathur/orca_mini_v1_dataset
dataset:openai/summarize_from_feedback
dataset:PygmalionAI/PIPPA
dataset:chargoddard/rpguild
dataset:lemonilia/LimaRP
Inference Endpoints
has_space
conversational
license: apache-2.0 | |
tags: | |
- Safetensors | |
- mistral | |
- text-generation-inference | |
- merge | |
- mistral | |
- 7b | |
- mistralai/Mistral-7B-Instruct-v0.1 | |
- chargoddard/loyal-piano-m7 | |
- transformers | |
- safetensors | |
- mistral | |
- text-generation | |
- en | |
- dataset:pankajmathur/orca_mini_v1_dataset | |
- dataset:openai/summarize_from_feedback | |
- dataset:PygmalionAI/PIPPA | |
- dataset:chargoddard/rpguild | |
- dataset:lemonilia/LimaRP | |
- license:cc-by-nc-4.0 | |
- autotrain_compatible | |
- endpoints_compatible | |
- has_space | |
- text-generation-inference | |
- region:us | |
# loyal-piano-m7-Mistral-7B-Instruct-v0.1 | |
loyal-piano-m7-Mistral-7B-Instruct-v0.1 is a merge of the following models: | |
* [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) | |
* [chargoddard/loyal-piano-m7](https://huggingface.co/chargoddard/loyal-piano-m7) | |
## 🧩 Configuration | |
```yaml | |
slices: | |
- sources: | |
- model: mistralai/Mistral-7B-Instruct-v0.1 | |
layer_range: [0, 32] | |
- model: chargoddard/loyal-piano-m7 | |
layer_range: [0, 32] | |
merge_method: slerp | |
base_model: mistralai/Mistral-7B-Instruct-v0.1 | |
parameters: | |
t: | |
- filter: self_attn | |
value: [0, 0.5, 0.3, 0.7, 1] | |
- filter: mlp | |
value: [1, 0.5, 0.7, 0.3, 0] | |
- value: 0.5 | |
dtype: bfloat16 | |
``` | |
## 💻 Usage | |
```python | |
!pip install -qU transformers accelerate | |
from transformers import AutoTokenizer | |
import transformers | |
import torch | |
model = "MaziyarPanahi/loyal-piano-m7-Mistral-7B-Instruct-v0.1" | |
messages = [{"role": "user", "content": "What is a large language model?"}] | |
tokenizer = AutoTokenizer.from_pretrained(model) | |
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) | |
pipeline = transformers.pipeline( | |
"text-generation", | |
model=model, | |
torch_dtype=torch.float16, | |
device_map="auto", | |
) | |
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) | |
print(outputs[0]["generated_text"]) | |
``` |