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[BIG] pytorch-transformers => transformers

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thomwolf
2019-09-26 10:15:53 +02:00
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examples/README.md
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@@ -13,7 +13,7 @@ similar API between the different models.
## Language model fine-tuning
Based on the script [`run_lm_finetuning.py`](https://github.com/huggingface/pytorch-transformers/blob/master/examples/run_lm_finetuning.py).
Based on the script [`run_lm_finetuning.py`](https://github.com/huggingface/transformers/blob/master/examples/run_lm_finetuning.py).
Fine-tuning the library models for language modeling on a text dataset for GPT, GPT-2, BERT and RoBERTa (DistilBERT
to be added soon). GPT and GPT-2 are fine-tuned using a causal language modeling (CLM) loss while BERT and RoBERTa
@@ -75,7 +75,7 @@ python run_lm_finetuning.py \
## Language generation
Based on the script [`run_generation.py`](https://github.com/huggingface/pytorch-transformers/blob/master/examples/run_generation.py).
Based on the script [`run_generation.py`](https://github.com/huggingface/transformers/blob/master/examples/run_generation.py).
Conditional text generation using the auto-regressive models of the library: GPT, GPT-2, Transformer-XL and XLNet.
A similar script is used for our official demo [Write With Transfomer](https://transformer.huggingface.co), where you
@@ -91,7 +91,7 @@ python run_generation.py \
## GLUE
Based on the script [`run_glue.py`](https://github.com/huggingface/pytorch-transformers/blob/master/examples/run_glue.py).
Based on the script [`run_glue.py`](https://github.com/huggingface/transformers/blob/master/examples/run_glue.py).
Fine-tuning the library models for sequence classification on the GLUE benchmark: [General Language Understanding
Evaluation](https://gluebenchmark.com/). This script can fine-tune the following models: BERT, XLM, XLNet and RoBERTa.
@@ -319,7 +319,7 @@ eval_loss = 0.44457291918821606
## SQuAD
Based on the script [`run_squad.py`](https://github.com/huggingface/pytorch-transformers/blob/master/examples/run_squad.py).
Based on the script [`run_squad.py`](https://github.com/huggingface/transformers/blob/master/examples/run_squad.py).
#### Fine-tuning on SQuAD