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Huggingface GPT-J Support

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Finetune's fork has unofficial support which we supported, but this is not compatible with models designed for the official version. In this update we let models decide which transformers backend to use, and fall back to Neo if they don't choose any. We also add the 6B to the menu and for the time being switch to the github version of transformers to be ahead of the waiting time. (Hopefully we can switch back to the conda version before merging upstream).
This commit is contained in:
henk717 2021-09-25 16:26:17 +02:00
parent 72669e0489
commit 7d35f825c6
2 changed files with 14 additions and 7 deletions
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16
aiserver.py
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@ -44,10 +44,11 @@ class colors:
# AI models # AI models
modellist = [ modellist = [
["Custom Neo (GPT-Neo / Converted GPT-J)", "NeoCustom", ""], ["Load a model from its directory", "NeoCustom", ""],
["Custom GPT-2 (eg CloverEdition)", "GPT2Custom", ""], ["Load an old GPT-2 model (eg CloverEdition)", "GPT2Custom", ""],
["GPT Neo 1.3B", "EleutherAI/gpt-neo-1.3B", "8GB"], ["GPT-Neo 1.3B", "EleutherAI/gpt-neo-1.3B", "8GB"],
["GPT Neo 2.7B", "EleutherAI/gpt-neo-2.7B", "16GB"], ["GPT-Neo 2.7B", "EleutherAI/gpt-neo-2.7B", "16GB"],
["GPT-J 6B (HF GIT Required)", "EleutherAI/gpt-j-6B", "24GB"],
["GPT-2", "gpt2", "1GB"], ["GPT-2", "gpt2", "1GB"],
["GPT-2 Med", "gpt2-medium", "2GB"], ["GPT-2 Med", "gpt2-medium", "2GB"],
["GPT-2 Large", "gpt2-large", "4GB"], ["GPT-2 Large", "gpt2-large", "4GB"],
@ -401,7 +402,12 @@ if(not vars.model in ["InferKit", "Colab", "OAI", "ReadOnly"]):
# If custom GPT Neo model was chosen # If custom GPT Neo model was chosen
if(vars.model == "NeoCustom"): if(vars.model == "NeoCustom"):
model = GPTNeoForCausalLM.from_pretrained(vars.custmodpth) model_config = open(vars.custmodpth + "/config.json", "r")
js = json.load(model_config)
if("architectures" in js):
model = vars.custmodpth
else:
model = GPTNeoForCausalLM.from_pretrained(vars.custmodpth)
tokenizer = GPT2Tokenizer.from_pretrained(vars.custmodpth) tokenizer = GPT2Tokenizer.from_pretrained(vars.custmodpth)
# Is CUDA available? If so, use GPU, otherwise fall back to CPU # Is CUDA available? If so, use GPU, otherwise fall back to CPU
if(vars.hascuda): if(vars.hascuda):

5
environments/huggingface.yml
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@ -11,7 +11,8 @@ dependencies:
- python=3.8.* - python=3.8.*
- cudatoolkit=11.1 - cudatoolkit=11.1
- tensorflow-gpu - tensorflow-gpu
- transformers
- pip - pip
- git
- pip: - pip:
- flask-cloudflared - flask-cloudflared
- git+https://github.com/huggingface/transformers#transformer