Instructions to use danyaljj/gpt2_question_generation_given_paragraph_answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use danyaljj/gpt2_question_generation_given_paragraph_answer with Transformers:

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

pipe = pipeline("text-generation", model="danyaljj/gpt2_question_generation_given_paragraph_answer")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("danyaljj/gpt2_question_generation_given_paragraph_answer")
model = AutoModelForCausalLM.from_pretrained("danyaljj/gpt2_question_generation_given_paragraph_answer")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use danyaljj/gpt2_question_generation_given_paragraph_answer with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "danyaljj/gpt2_question_generation_given_paragraph_answer"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "danyaljj/gpt2_question_generation_given_paragraph_answer",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/danyaljj/gpt2_question_generation_given_paragraph_answer

SGLang

How to use danyaljj/gpt2_question_generation_given_paragraph_answer 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 "danyaljj/gpt2_question_generation_given_paragraph_answer" \
    --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": "danyaljj/gpt2_question_generation_given_paragraph_answer",
		"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 "danyaljj/gpt2_question_generation_given_paragraph_answer" \
        --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": "danyaljj/gpt2_question_generation_given_paragraph_answer",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use danyaljj/gpt2_question_generation_given_paragraph_answer with Docker Model Runner:
```
docker model run hf.co/danyaljj/gpt2_question_generation_given_paragraph_answer
```

danyaljj commited on Jun 17, 2021

Commit

726ce30

1 Parent(s): 777ef85

update

Browse files

Files changed (9) hide show

config.json +37 -0
last_eval_metrics.json +1 -0
merges.txt +0 -0
metrics.json +1 -0
pytorch_model.bin +3 -0
special_tokens_map.json +1 -0
tokenizer_config.json +1 -0
training_args.bin +3 -0
vocab.json +0 -0

config.json ADDED Viewed

	@@ -0,0 +1,37 @@

+{
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "finetuning_task": null,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_layer": 12,
+  "n_positions": 1024,
+  "num_labels": 1,
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "pruned_heads": {},
+  "resid_pdrop": 0.1,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "torchscript": false,
+  "vocab_size": 50257
+}

last_eval_metrics.json ADDED Viewed

	@@ -0,0 +1 @@


1	+ perplexity = 5.620667457580566

merges.txt ADDED Viewed

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metrics.json ADDED Viewed

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1	+ {"2000.perplexity": 5.736455917358398, "4000.perplexity": 5.489027976989746, "6000.perplexity": 5.511296272277832, "8000.perplexity": 5.422763347625732, "10000.perplexity": 5.544301986694336, "12000.perplexity": 5.620221138000488, "best_perp": 5.422763347625732, "best_perp_step": 8000}

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special_tokens_map.json ADDED Viewed

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1	+ {"bos_token": "<\|endoftext\|>", "eos_token": "<\|endoftext\|>", "unk_token": "<\|endoftext\|>"}

tokenizer_config.json ADDED Viewed

	@@ -0,0 +1 @@


1	+ {"do_lower_case": false, "max_len": 1024, "init_inputs": []}

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vocab.json ADDED Viewed

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