Instructions to use GItaf/bert2bert-with-cross-attn-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use GItaf/bert2bert-with-cross-attn-decoder with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="GItaf/bert2bert-with-cross-attn-decoder")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("GItaf/bert2bert-with-cross-attn-decoder")
model = AutoModelForCausalLM.from_pretrained("GItaf/bert2bert-with-cross-attn-decoder", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use GItaf/bert2bert-with-cross-attn-decoder with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "GItaf/bert2bert-with-cross-attn-decoder"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "GItaf/bert2bert-with-cross-attn-decoder",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/GItaf/bert2bert-with-cross-attn-decoder

SGLang

How to use GItaf/bert2bert-with-cross-attn-decoder with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "GItaf/bert2bert-with-cross-attn-decoder" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "GItaf/bert2bert-with-cross-attn-decoder",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "GItaf/bert2bert-with-cross-attn-decoder" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "GItaf/bert2bert-with-cross-attn-decoder",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use GItaf/bert2bert-with-cross-attn-decoder with Docker Model Runner:
```
docker model run hf.co/GItaf/bert2bert-with-cross-attn-decoder
```

BrandonC8310 commited on Sep 7, 2022

Commit

423d12e

1 Parent(s): 70c46f7

add

Browse files

Files changed (6) hide show

config.json +27 -0
special_tokens_map.json +7 -0
tokenizer.json +0 -0
tokenizer_config.json +14 -0
training_args.bin +0 -0
vocab.txt +0 -0

config.json ADDED Viewed

	@@ -0,0 +1,27 @@

+{
+  "_name_or_path": "bert-base-uncased",
+  "architectures": [
+    "BertLMHeadModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "is_decoder": true,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.21.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

special_tokens_map.json ADDED Viewed

	@@ -0,0 +1,7 @@

+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer.json ADDED Viewed

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tokenizer_config.json ADDED Viewed

	@@ -0,0 +1,14 @@

+{
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "name_or_path": "bert-base-uncased",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "special_tokens_map_file": null,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin ADDED Viewed

Binary file (3.31 kB). View file

vocab.txt ADDED Viewed

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