Habana / distilbert-base-uncased

huggingface.co
Total runs: 9.0K
24-hour runs: -116
7-day runs: 667
30-day runs: 761
Model's Last Updated: 8月 18 2023

Introduction of distilbert-base-uncased

Model Details of distilbert-base-uncased

Optimum Habana is the interface between the Hugging Face Transformers and Diffusers libraries and Habana's Gaudi processor (HPU). It provides a set of tools enabling easy and fast model loading, training and inference on single- and multi-HPU settings for different downstream tasks. Learn more about how to take advantage of the power of Habana HPUs to train and deploy Transformers and Diffusers models at hf.co/hardware/habana .

DistilBERT Base model HPU configuration

This model only contains the GaudiConfig file for running the distilbert-base-uncased model on Habana's Gaudi processors (HPU).

This model contains no model weights, only a GaudiConfig.

This enables to specify:

  • use_fused_adam : whether to use Habana's custom AdamW implementation
  • use_fused_clip_norm : whether to use Habana's fused gradient norm clipping operator
  • use_torch_autocast : whether to use Torch Autocast for managing mixed precision
Usage

The model is instantiated the same way as in the Transformers library. The only difference is that there are a few new training arguments specific to HPUs.
It is strongly recommended to train this model doing bf16 mixed-precision training for optimal performance and accuracy.

Here is a question-answering example script to fine-tune a model on SQuAD. You can run it with DistilBERT with the following command:

python run_qa.py \
  --model_name_or_path distilbert-base-uncased \
  --gaudi_config_name Habana/distilbert-base-uncased \
  --dataset_name squad \
  --do_train \
  --do_eval \
  --per_device_train_batch_size 8 \
  --per_device_eval_batch_size 8 \
  --learning_rate 5e-5 \
  --num_train_epochs 3 \
  --max_seq_length 384 \
  --output_dir /tmp/squad/ \
  --use_habana \
  --use_lazy_mode \
  --throughput_warmup_steps 3 \
  --bf16

Check the documentation out for more advanced usage and examples.

Runs of Habana distilbert-base-uncased on huggingface.co

9.0K
Total runs
-116
24-hour runs
-540
3-day runs
667
7-day runs
761
30-day runs

More Information About distilbert-base-uncased huggingface.co Model

More distilbert-base-uncased license Visit here:

https://choosealicense.com/licenses/apache-2.0

distilbert-base-uncased huggingface.co

distilbert-base-uncased huggingface.co is an AI model on huggingface.co that provides distilbert-base-uncased's model effect (), which can be used instantly with this Habana distilbert-base-uncased model. huggingface.co supports a free trial of the distilbert-base-uncased model, and also provides paid use of the distilbert-base-uncased. Support call distilbert-base-uncased model through api, including Node.js, Python, http.

distilbert-base-uncased huggingface.co Url

https://huggingface.co/Habana/distilbert-base-uncased

Habana distilbert-base-uncased online free

distilbert-base-uncased huggingface.co is an online trial and call api platform, which integrates distilbert-base-uncased's modeling effects, including api services, and provides a free online trial of distilbert-base-uncased, you can try distilbert-base-uncased online for free by clicking the link below.

Habana distilbert-base-uncased online free url in huggingface.co:

https://huggingface.co/Habana/distilbert-base-uncased

distilbert-base-uncased install

distilbert-base-uncased is an open source model from GitHub that offers a free installation service, and any user can find distilbert-base-uncased on GitHub to install. At the same time, huggingface.co provides the effect of distilbert-base-uncased install, users can directly use distilbert-base-uncased installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

distilbert-base-uncased install url in huggingface.co:

https://huggingface.co/Habana/distilbert-base-uncased

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