allennlp
mesh-transformer-jax
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| allennlp | mesh-transformer-jax | |
|---|---|---|
| 13 | 52 | |
| 11,337 | 6,213 | |
| - | - | |
| 8.4 | 0.0 | |
| over 1 year ago | over 1 year ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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allennlp
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How to solve ConfigurationError using HuggingFace Token Classifier
No clue. So what I did was google the error. Here's what I found: https://github.com/allenai/allennlp/issues/4319
- AllenNLP will be unmaintained in December
- AllenNLP Is EOL
- Any recommendation for the replacement of the toolkit jiant? [Research] [Discussion]
- Cedille, the largest French language model, open source with a freely accessible playground
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[P] Cedille, the largest French language model (6b), released in open source
Another aspect we had fun with is dataset filtering. We have run the whole C4 French dataset through the Detoxify classifier to clean it up 🤬
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Any allennlp users in this sub?
https://github.com/allenai/allennlp/discussions looks active
- Multilingual C4 (mC4) Dataset now released
- C4 dataset released (800GB Common Crawl-derived text; T5 training data)
mesh-transformer-jax
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Large Language Models: Compairing Gen2/Gen3 Models (GPT-3, GPT-J, MT5 and More)
GPT-J is a LLM case study with two goals: Training a LLM with a data source containing unique material, and using the training frameworkMesh Transformer JAX to achieve a high training efficiency through parallelization. There is no research paper about GPT-J, but on its GitHub pages, the model, different checkpoints, and the complete source code for training is given.
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[R] Parallel Attention and Feed-Forward Net Design for Pre-training and Inference on Transformers
This idea has already been proposed in ViT-22B and GPT-J-6B.
- Show HN: Finetune LLaMA-7B on commodity GPUs using your own text
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[D] An Instruct Version Of GPT-J Using Stanford Alpaca's Dataset
Sure. Here's the repo I used for the fine-tuning: https://github.com/kingoflolz/mesh-transformer-jax. I used 5 epochs, and appart from that I kept the default parameters in the repo.
- Boss wants me to use ChatGPT for work, but I refuse to input my personal phone number. Any advice?
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Let's build GPT: from scratch, in code, spelled out by Andrej Karpathy
You can skip to step 4 using something like GPT-J as far as I understand: https://github.com/kingoflolz/mesh-transformer-jax#links
The pretrained model is already available.
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Best coding model?
The Github repo suggests it's possible you can change the number of checkpoints to make it run on a GPU.
- Ask HN: What language models can I fine-tune at home?
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selfhosted/ open-source ChatGPT alternative?
GPT-J, which uses mesh-transformer-jax: https://github.com/kingoflolz/mesh-transformer-jax
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GPT-J, an open-source alternative to GPT-3
They hinted at it in the screenshot, but the goods are linked from the https://6b.eleuther.ai page: https://github.com/kingoflolz/mesh-transformer-jax#gpt-j-6b (Apache 2)
What are some alternatives?
cedille-ai - ✒️ Cedille is a large French language model (6B), released under an open-source license
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
tensorflow - An Open Source Machine Learning Framework for Everyone
lm-evaluation-harness - A framework for few-shot evaluation of language models.
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
python-sutime - Python wrapper for Stanford CoreNLP's SUTime
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
PaddleHub - Awesome pre-trained models toolkit based on PaddlePaddle. (400+ models including Image, Text, Audio, Video and Cross-Modal with Easy Inference & Serving)
KoboldAI-Client
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
alpaca-lora - Instruct-tune LLaMA on consumer hardware