File size: 2,275 Bytes
84a751e 6abd23d 84a751e 6abd23d 84a751e 6abd23d 84a751e 6abd23d 84a751e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 |
---
language:
- en
datasets:
- natural_instructions
- the_pile
- cot
- Muennighoff/P3
tags:
- ctranslate2
- int8
- float16
- gpt
pipeline_tag: text-generation
inference:
parameters:
temperature: 0.1
widget:
- text: "Is this review positive or negative? Review: Best cast iron skillet you will ever buy. Answer:"
example_title: "Sentiment analysis"
- text: "Where is Zurich? Ans:"
example_title: "Question Answering"
---
# # Fast-Inference with Ctranslate2
Speedup inference while reducing memory by 2x-4x using int8 inference in C++ on CPU or GPU.
quantized version of [togethercomputer/GPT-JT-6B-v0](https://huggingface.co/togethercomputer/GPT-JT-6B-v0)
```bash
pip install hf-hub-ctranslate2>=2.0.6
```
Converted on 2023-05-19 using
```
ct2-transformers-converter --model togethercomputer/GPT-JT-6B-v0 --output_dir /home/michael/tmp-ct2fast-GPT-JT-6B-v0 --force --copy_files merges.txt tokenizer.json README.md tokenizer_config.json vocab.json special_tokens_map.json added_tokens.json .gitattributes --quantization float16
```
Checkpoint compatible to [ctranslate2>=3.13.0](https://github.com/OpenNMT/CTranslate2) and [hf-hub-ctranslate2>=2.0.6](https://github.com/michaelfeil/hf-hub-ctranslate2)
- `compute_type=int8_float16` for `device="cuda"`
- `compute_type=int8` for `device="cpu"`
```python
from hf_hub_ctranslate2 import TranslatorCT2fromHfHub, GeneratorCT2fromHfHub
from transformers import AutoTokenizer
model_name = "michaelfeil/ct2fast-GPT-JT-6B-v0"
# use either TranslatorCT2fromHfHub or GeneratorCT2fromHfHub here, depending on model.
model = GeneratorCT2fromHfHub(
# load in int8 on CUDA
model_name_or_path=model_name,
device="cuda",
compute_type="int8_float16",
tokenizer=AutoTokenizer.from_pretrained("togethercomputer/GPT-JT-6B-v0")
)
outputs = model.generate(
text=["How do you call a fast Flan-ingo?", "User: How are you doing? Bot:"],
)
print(outputs)
```
# Licence and other remarks:
This is just a quantized version. Licence conditions are intended to be idential to original huggingface repo.
# Original description
# Quick Start
```python
from transformers import pipeline
pipe = pipeline(model='togethercomputer/GPT-JT-6B-v0')
pipe("Where is Zurich? Ans:")
``` |