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Update API inference documentation (automated)
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hanouticelina authored and github-actions[bot] committed Dec 26, 2024
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5 changes: 5 additions & 0 deletions changed_files.txt
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docs/api-inference/tasks/question-answering.md
docs/api-inference/tasks/table-question-answering.md
docs/api-inference/tasks/zero-shot-classification.md
scripts/api-inference/package.json
scripts/api-inference/pnpm-lock.yaml
1 change: 0 additions & 1 deletion docs/api-inference/tasks/question-answering.md
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Expand Up @@ -26,7 +26,6 @@ For more details about the `question-answering` task, check out its [dedicated p

- [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2): A robust baseline model for most question answering domains.
- [distilbert/distilbert-base-cased-distilled-squad](https://huggingface.co/distilbert/distilbert-base-cased-distilled-squad): Small yet robust model that can answer questions.
- [google/tapas-base-finetuned-wtq](https://huggingface.co/google/tapas-base-finetuned-wtq): A special model that can answer questions from tables.

Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=question-answering&sort=trending).

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7 changes: 3 additions & 4 deletions docs/api-inference/tasks/table-question-answering.md
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Expand Up @@ -24,7 +24,6 @@ For more details about the `table-question-answering` task, check out its [dedic

### Recommended models

- [google/tapas-base-finetuned-wtq](https://huggingface.co/google/tapas-base-finetuned-wtq): A robust table question answering model.

Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=table-question-answering&sort=trending).

Expand All @@ -35,7 +34,7 @@ Explore all available models and find the one that suits you best [here](https:/

<curl>
```bash
curl https://api-inference.huggingface.co/models/google/tapas-base-finetuned-wtq \
curl https://api-inference.huggingface.co/models/<REPO_ID> \
-X POST \
-d '{"inputs": { "query": "How many stars does the transformers repository have?", "table": { "Repository": ["Transformers", "Datasets", "Tokenizers"], "Stars": ["36542", "4512", "3934"], "Contributors": ["651", "77", "34"], "Programming language": [ "Python", "Python", "Rust, Python and NodeJS" ] } }}' \
-H 'Content-Type: application/json' \
Expand All @@ -47,7 +46,7 @@ curl https://api-inference.huggingface.co/models/google/tapas-base-finetuned-wtq
```py
import requests

API_URL = "https://api-inference.huggingface.co/models/google/tapas-base-finetuned-wtq"
API_URL = "https://api-inference.huggingface.co/models/<REPO_ID>"
headers = {"Authorization": "Bearer hf_***"}

def query(payload):
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```js
async function query(data) {
const response = await fetch(
"https://api-inference.huggingface.co/models/google/tapas-base-finetuned-wtq",
"https://api-inference.huggingface.co/models/<REPO_ID>",
{
headers: {
Authorization: "Bearer hf_***",
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1 change: 0 additions & 1 deletion docs/api-inference/tasks/zero-shot-classification.md
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Expand Up @@ -25,7 +25,6 @@ For more details about the `zero-shot-classification` task, check out its [dedic
### Recommended models

- [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli): Powerful zero-shot text classification model.
- [MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7): Powerful zero-shot multilingual text classification model that can accomplish multiple tasks.

Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=zero-shot-classification&sort=trending).

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2 changes: 1 addition & 1 deletion scripts/api-inference/package.json
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"author": "",
"license": "ISC",
"dependencies": {
"@huggingface/tasks": "^0.13.11",
"@huggingface/tasks": "^0.13.13",
"@types/node": "^22.5.0",
"handlebars": "^4.7.8",
"node": "^20.17.0",
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10 changes: 5 additions & 5 deletions scripts/api-inference/pnpm-lock.yaml

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