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---
license: mit
datasets:
- databricks/databricks-dolly-15k
language:
- en
pipeline_tag: text-generation
tags:
- dolly
- dolly-v2
- instruct
- sharded
widget:
- text: Imagine Einstein was part of a comedy duo. What would be their stage name?
example_title: Einstein's comedy duo
- text: What do you think Einstein's favorite Swiss chocolate brand would be?
example_title: Einstein's chocolate
- text: If Einstein were to enter a yodeling competition in Switzerland, what
would his yodel sound like?
example_title: Einstein's yodel
- text: If Einstein had to create a Swiss-themed superhero, what would their name
and superpower be?
example_title: Swiss superhero
- text: What kind of wild party would Einstein throw at ETH Zurich?
example_title: Einstein's party
- text: If Einstein had a pet Swiss cow, what would he name it and why?
example_title: Einstein's cow
- text: You've discovered a secret Swiss cheese that grants the power of genius.
How would you use it to become the next Einstein?
example_title: Genius cheese
inference:
parameters:
max_length: 64
min_length: 32
---
# dolly-v2-7b: sharded checkpoint
<a href="https://colab.research.google.com/gist/pszemraj/6eb7ccce28ea6aa07b8ec86388ac010e/sharded-instruction-model-playground.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
This is a sharded checkpoint (with ~4GB shards) of the `databricks/dolly-v2-7b` model. Refer to the [original model](https://huggingface.co/databricks/dolly-v2-7b) for all details.
- this enables low-RAM loading, i.e. Colab :)
## Basic Usage
install `transformers`, `accelerate`, and `bitsandbytes`.
```bash
pip install -U -q transformers bitsandbytes accelerate
```
Load the model in 8bit, then [run inference](https://huggingface.co/docs/transformers/generation_strategies#contrastive-search):
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
model_name = "ethzanalytics/dolly-v2-7b-sharded"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name, load_in_8bit=True, device_map="auto",
)
``` |