Skip to content

Commit 3519e41

Browse files
HuggingFaceInfraWauplin
HuggingFaceInfra
and
Wauplin
authored
Update Inference Providers documentation (automated) (#1811)
Co-authored-by: Wauplin <[email protected]>
1 parent d4896a0 commit 3519e41

18 files changed

+41
-72
lines changed

‎docs/inference-providers/providers/featherless-ai.md‎

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -52,7 +52,7 @@ Find out more about Chat Completion (LLM) [here](../tasks/chat-completion).
5252

5353
<InferenceSnippet
5454
pipeline=text-generation
55-
providersMapping={ {"featherless-ai":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"} } }
55+
providersMapping={ {"featherless-ai":{"modelId":"mistralai/Magistral-Small-2506","providerModelId":"mistralai/Magistral-Small-2506"} } }
5656
conversational />
5757

5858

@@ -62,7 +62,7 @@ Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
6262

6363
<InferenceSnippet
6464
pipeline=image-text-to-text
65-
providersMapping={ {"featherless-ai":{"modelId":"google/medgemma-4b-it","providerModelId":"google/medgemma-4b-it"} } }
65+
providersMapping={ {"featherless-ai":{"modelId":"CEIA-UFG/Gemma-3-Gaia-PT-BR-4b-it","providerModelId":"CEIA-UFG/Gemma-3-Gaia-PT-BR-4b-it"} } }
6666
conversational />
6767

6868

@@ -72,6 +72,6 @@ Find out more about Text Generation [here](../tasks/text_generation).
7272

7373
<InferenceSnippet
7474
pipeline=text-generation
75-
providersMapping={ {"featherless-ai":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"} } }
75+
providersMapping={ {"featherless-ai":{"modelId":"mistralai/Magistral-Small-2506","providerModelId":"mistralai/Magistral-Small-2506"} } }
7676
/>
7777

‎docs/inference-providers/providers/hf-inference.md‎

Lines changed: 6 additions & 46 deletions
Original file line numberDiff line numberDiff line change
@@ -45,26 +45,6 @@ If you are interested in deploying models to a dedicated and autoscaling infrast
4545
## Supported tasks
4646

4747

48-
### Automatic Speech Recognition
49-
50-
Find out more about Automatic Speech Recognition [here](../tasks/automatic_speech_recognition).
51-
52-
<InferenceSnippet
53-
pipeline=automatic-speech-recognition
54-
providersMapping={ {"hf-inference":{"modelId":"openai/whisper-large-v3","providerModelId":"openai/whisper-large-v3"} } }
55-
/>
56-
57-
58-
### Chat Completion (VLM)
59-
60-
Find out more about Chat Completion (VLM) [here](../tasks/chat-completion).
61-
62-
<InferenceSnippet
63-
pipeline=image-text-to-text
64-
providersMapping={ {"hf-inference":{"modelId":"meta-llama/Llama-3.2-11B-Vision-Instruct","providerModelId":"meta-llama/Llama-3.2-11B-Vision-Instruct"} } }
65-
conversational />
66-
67-
6848
### Feature Extraction
6949

7050
Find out more about Feature Extraction [here](../tasks/feature_extraction).
@@ -91,7 +71,7 @@ Find out more about Image Classification [here](../tasks/image_classification).
9171

9272
<InferenceSnippet
9373
pipeline=image-classification
94-
providersMapping={ {"hf-inference":{"modelId":"dima806/fairface_age_image_detection","providerModelId":"dima806/fairface_age_image_detection"} } }
74+
providersMapping={ {"hf-inference":{"modelId":"Falconsai/nsfw_image_detection","providerModelId":"Falconsai/nsfw_image_detection"} } }
9575
/>
9676

9777

@@ -101,17 +81,7 @@ Find out more about Image Segmentation [here](../tasks/image_segmentation).
10181

10282
<InferenceSnippet
10383
pipeline=image-segmentation
104-
providersMapping={ {"hf-inference":{"modelId":"nvidia/segformer-b0-finetuned-ade-512-512","providerModelId":"nvidia/segformer-b0-finetuned-ade-512-512"} } }
105-
/>
106-
107-
108-
### Object Detection
109-
110-
Find out more about Object Detection [here](../tasks/object_detection).
111-
112-
<InferenceSnippet
113-
pipeline=object-detection
114-
providersMapping={ {"hf-inference":{"modelId":"facebook/detr-resnet-50","providerModelId":"facebook/detr-resnet-50"} } }
84+
providersMapping={ {"hf-inference":{"modelId":"mattmdjaga/segformer_b2_clothes","providerModelId":"mattmdjaga/segformer_b2_clothes"} } }
11585
/>
11686

11787

@@ -121,7 +91,7 @@ Find out more about Question Answering [here](../tasks/question_answering).
12191

12292
<InferenceSnippet
12393
pipeline=question-answering
124-
providersMapping={ {"hf-inference":{"modelId":"uer/roberta-base-chinese-extractive-qa","providerModelId":"uer/roberta-base-chinese-extractive-qa"} } }
94+
providersMapping={ {"hf-inference":{"modelId":"deepset/roberta-base-squad2","providerModelId":"deepset/roberta-base-squad2"} } }
12595
/>
12696

12797

@@ -141,7 +111,7 @@ Find out more about Table Question Answering [here](../tasks/table_question_answ
141111

142112
<InferenceSnippet
143113
pipeline=table-question-answering
144-
providersMapping={ {"hf-inference":{"modelId":"google/tapas-large-finetuned-wtq","providerModelId":"google/tapas-large-finetuned-wtq"} } }
114+
providersMapping={ {"hf-inference":{"modelId":"google/tapas-base-finetuned-wtq","providerModelId":"google/tapas-base-finetuned-wtq"} } }
145115
/>
146116

147117

@@ -155,23 +125,13 @@ Find out more about Text Classification [here](../tasks/text_classification).
155125
/>
156126

157127

158-
### Text To Image
159-
160-
Find out more about Text To Image [here](../tasks/text_to_image).
161-
162-
<InferenceSnippet
163-
pipeline=text-to-image
164-
providersMapping={ {"hf-inference":{"modelId":"black-forest-labs/FLUX.1-dev","providerModelId":"black-forest-labs/FLUX.1-dev"} } }
165-
/>
166-
167-
168128
### Token Classification
169129

170130
Find out more about Token Classification [here](../tasks/token_classification).
171131

172132
<InferenceSnippet
173133
pipeline=token-classification
174-
providersMapping={ {"hf-inference":{"modelId":"DeepMount00/Italian_NER_XXL","providerModelId":"DeepMount00/Italian_NER_XXL"} } }
134+
providersMapping={ {"hf-inference":{"modelId":"dslim/bert-base-NER","providerModelId":"dslim/bert-base-NER"} } }
175135
/>
176136

177137

@@ -181,6 +141,6 @@ Find out more about Translation [here](../tasks/translation).
181141

182142
<InferenceSnippet
183143
pipeline=translation
184-
providersMapping={ {"hf-inference":{"modelId":"Helsinki-NLP/opus-mt-zh-en","providerModelId":"Helsinki-NLP/opus-mt-zh-en"} } }
144+
providersMapping={ {"hf-inference":{"modelId":"google-t5/t5-base","providerModelId":"google-t5/t5-base"} } }
185145
/>
186146

‎docs/inference-providers/tasks/automatic-speech-recognition.md‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -38,7 +38,7 @@ Explore all available models and find the one that suits you best [here](https:/
3838

3939
<InferenceSnippet
4040
pipeline=automatic-speech-recognition
41-
providersMapping={ {"fal-ai":{"modelId":"openai/whisper-large-v3","providerModelId":"fal-ai/whisper"},"hf-inference":{"modelId":"openai/whisper-large-v3","providerModelId":"openai/whisper-large-v3"}} }
41+
providersMapping={ {"fal-ai":{"modelId":"openai/whisper-large-v3","providerModelId":"fal-ai/whisper"}} }
4242
/>
4343

4444

‎docs/inference-providers/tasks/chat-completion.md‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -63,7 +63,7 @@ The API supports:
6363

6464
<InferenceSnippet
6565
pipeline=text-generation
66-
providersMapping={ {"cerebras":{"modelId":"meta-llama/Llama-3.3-70B-Instruct","providerModelId":"llama-3.3-70b"},"cohere":{"modelId":"CohereLabs/c4ai-command-r-plus","providerModelId":"command-r-plus-04-2024"},"featherless-ai":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"},"fireworks-ai":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"accounts/fireworks/models/deepseek-r1-0528"},"groq":{"modelId":"meta-llama/Llama-3.3-70B-Instruct","providerModelId":"llama-3.3-70b-versatile"},"hyperbolic":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"},"nebius":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"},"novita":{"modelId":"MiniMaxAI/MiniMax-M1-80k","providerModelId":"minimaxai/minimax-m1-80k"},"nscale":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"meta-llama/Llama-3.1-8B-Instruct"},"sambanova":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"DeepSeek-R1-0528"},"together":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1"}} }
66+
providersMapping={ {"cerebras":{"modelId":"meta-llama/Llama-3.3-70B-Instruct","providerModelId":"llama-3.3-70b"},"cohere":{"modelId":"CohereLabs/c4ai-command-r-plus","providerModelId":"command-r-plus-04-2024"},"featherless-ai":{"modelId":"mistralai/Magistral-Small-2506","providerModelId":"mistralai/Magistral-Small-2506"},"fireworks-ai":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"accounts/fireworks/models/deepseek-r1-0528"},"groq":{"modelId":"meta-llama/Llama-3.3-70B-Instruct","providerModelId":"llama-3.3-70b-versatile"},"hyperbolic":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"},"nebius":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1-0528"},"novita":{"modelId":"MiniMaxAI/MiniMax-M1-80k","providerModelId":"minimaxai/minimax-m1-80k"},"nscale":{"modelId":"meta-llama/Llama-3.1-8B-Instruct","providerModelId":"meta-llama/Llama-3.1-8B-Instruct"},"sambanova":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"DeepSeek-R1-0528"},"together":{"modelId":"deepseek-ai/DeepSeek-R1-0528","providerModelId":"deepseek-ai/DeepSeek-R1"}} }
6767
conversational />
6868

6969

@@ -73,7 +73,7 @@ conversational />
7373

7474
<InferenceSnippet
7575
pipeline=image-text-to-text
76-
providersMapping={ {"cerebras":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"llama-4-scout-17b-16e-instruct"},"cohere":{"modelId":"CohereLabs/aya-vision-8b","providerModelId":"c4ai-aya-vision-8b"},"featherless-ai":{"modelId":"google/medgemma-4b-it","providerModelId":"google/medgemma-4b-it"},"fireworks-ai":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"accounts/fireworks/models/llama4-scout-instruct-basic"},"groq":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/llama-4-scout-17b-16e-instruct"},"hf-inference":{"modelId":"meta-llama/Llama-3.2-11B-Vision-Instruct","providerModelId":"meta-llama/Llama-3.2-11B-Vision-Instruct"},"hyperbolic":{"modelId":"Qwen/Qwen2.5-VL-7B-Instruct","providerModelId":"Qwen/Qwen2.5-VL-7B-Instruct"},"nebius":{"modelId":"google/gemma-3-27b-it","providerModelId":"google/gemma-3-27b-it-fast"},"novita":{"modelId":"baidu/ERNIE-4.5-VL-424B-A47B-Base-PT","providerModelId":"baidu/ernie-4.5-vl-424b-a47b"},"nscale":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"},"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-Instruct"},"together":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"}} }
76+
providersMapping={ {"cerebras":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"llama-4-scout-17b-16e-instruct"},"cohere":{"modelId":"CohereLabs/aya-vision-8b","providerModelId":"c4ai-aya-vision-8b"},"featherless-ai":{"modelId":"CEIA-UFG/Gemma-3-Gaia-PT-BR-4b-it","providerModelId":"CEIA-UFG/Gemma-3-Gaia-PT-BR-4b-it"},"fireworks-ai":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"accounts/fireworks/models/llama4-scout-instruct-basic"},"groq":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/llama-4-scout-17b-16e-instruct"},"hyperbolic":{"modelId":"Qwen/Qwen2.5-VL-7B-Instruct","providerModelId":"Qwen/Qwen2.5-VL-7B-Instruct"},"nebius":{"modelId":"google/gemma-3-27b-it","providerModelId":"google/gemma-3-27b-it-fast"},"novita":{"modelId":"baidu/ERNIE-4.5-VL-424B-A47B-Base-PT","providerModelId":"baidu/ernie-4.5-vl-424b-a47b"},"nscale":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"},"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-Instruct"},"together":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"}} }
7777
conversational />
7878

7979

‎docs/inference-providers/tasks/feature-extraction.md‎

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -29,6 +29,7 @@ For more details about the `feature-extraction` task, check out its [dedicated p
2929

3030
### Recommended models
3131

32+
- [thenlper/gte-large](https://huggingface.co/thenlper/gte-large): A powerful feature extraction model for natural language processing tasks.
3233

3334
Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=feature-extraction&sort=trending).
3435

‎docs/inference-providers/tasks/image-classification.md‎

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -25,6 +25,7 @@ For more details about the `image-classification` task, check out its [dedicated
2525
### Recommended models
2626

2727
- [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224): A strong image classification model.
28+
- [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224): A robust image classification model.
2829
- [facebook/convnext-large-224](https://huggingface.co/facebook/convnext-large-224): A strong image classification model.
2930

3031
Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=image-classification&sort=trending).
@@ -34,7 +35,7 @@ Explore all available models and find the one that suits you best [here](https:/
3435

3536
<InferenceSnippet
3637
pipeline=image-classification
37-
providersMapping={ {"hf-inference":{"modelId":"dima806/fairface_age_image_detection","providerModelId":"dima806/fairface_age_image_detection"}} }
38+
providersMapping={ {"hf-inference":{"modelId":"Falconsai/nsfw_image_detection","providerModelId":"Falconsai/nsfw_image_detection"}} }
3839
/>
3940

4041

‎docs/inference-providers/tasks/image-segmentation.md‎

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -24,6 +24,7 @@ For more details about the `image-segmentation` task, check out its [dedicated p
2424

2525
### Recommended models
2626

27+
- [openmmlab/upernet-convnext-small](https://huggingface.co/openmmlab/upernet-convnext-small): Solid semantic segmentation model trained on ADE20k.
2728

2829
Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=image-segmentation&sort=trending).
2930

@@ -32,7 +33,7 @@ Explore all available models and find the one that suits you best [here](https:/
3233

3334
<InferenceSnippet
3435
pipeline=image-segmentation
35-
providersMapping={ {"hf-inference":{"modelId":"nvidia/segformer-b0-finetuned-ade-512-512","providerModelId":"nvidia/segformer-b0-finetuned-ade-512-512"}} }
36+
providersMapping={ {"hf-inference":{"modelId":"mattmdjaga/segformer_b2_clothes","providerModelId":"mattmdjaga/segformer_b2_clothes"}} }
3637
/>
3738

3839

‎docs/inference-providers/tasks/image-text-to-text.md‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -33,7 +33,7 @@ Explore all available models and find the one that suits you best [here](https:/
3333

3434
<InferenceSnippet
3535
pipeline=image-text-to-text
36-
providersMapping={ {"cerebras":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"llama-4-scout-17b-16e-instruct"},"cohere":{"modelId":"CohereLabs/aya-vision-8b","providerModelId":"c4ai-aya-vision-8b"},"featherless-ai":{"modelId":"google/medgemma-4b-it","providerModelId":"google/medgemma-4b-it"},"fireworks-ai":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"accounts/fireworks/models/llama4-scout-instruct-basic"},"groq":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/llama-4-scout-17b-16e-instruct"},"hf-inference":{"modelId":"meta-llama/Llama-3.2-11B-Vision-Instruct","providerModelId":"meta-llama/Llama-3.2-11B-Vision-Instruct"},"hyperbolic":{"modelId":"Qwen/Qwen2.5-VL-7B-Instruct","providerModelId":"Qwen/Qwen2.5-VL-7B-Instruct"},"nebius":{"modelId":"google/gemma-3-27b-it","providerModelId":"google/gemma-3-27b-it-fast"},"novita":{"modelId":"baidu/ERNIE-4.5-VL-424B-A47B-Base-PT","providerModelId":"baidu/ernie-4.5-vl-424b-a47b"},"nscale":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"},"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-Instruct"},"together":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"}} }
36+
providersMapping={ {"cerebras":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"llama-4-scout-17b-16e-instruct"},"cohere":{"modelId":"CohereLabs/aya-vision-8b","providerModelId":"c4ai-aya-vision-8b"},"featherless-ai":{"modelId":"CEIA-UFG/Gemma-3-Gaia-PT-BR-4b-it","providerModelId":"CEIA-UFG/Gemma-3-Gaia-PT-BR-4b-it"},"fireworks-ai":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"accounts/fireworks/models/llama4-scout-instruct-basic"},"groq":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/llama-4-scout-17b-16e-instruct"},"hyperbolic":{"modelId":"Qwen/Qwen2.5-VL-7B-Instruct","providerModelId":"Qwen/Qwen2.5-VL-7B-Instruct"},"nebius":{"modelId":"google/gemma-3-27b-it","providerModelId":"google/gemma-3-27b-it-fast"},"novita":{"modelId":"baidu/ERNIE-4.5-VL-424B-A47B-Base-PT","providerModelId":"baidu/ernie-4.5-vl-424b-a47b"},"nscale":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"},"sambanova":{"modelId":"meta-llama/Llama-4-Maverick-17B-128E-Instruct","providerModelId":"Llama-4-Maverick-17B-128E-Instruct"},"together":{"modelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct","providerModelId":"meta-llama/Llama-4-Scout-17B-16E-Instruct"}} }
3737
conversational />
3838

3939

‎docs/inference-providers/tasks/object-detection.md‎

Lines changed: 1 addition & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -24,17 +24,13 @@ For more details about the `object-detection` task, check out its [dedicated pag
2424

2525
### Recommended models
2626

27-
- [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50): Solid object detection model pre-trained on the COCO 2017 dataset.
2827

2928
Explore all available models and find the one that suits you best [here](https://huggingface.co/models?inference=warm&pipeline_tag=object-detection&sort=trending).
3029

3130
### Using the API
3231

3332

34-
<InferenceSnippet
35-
pipeline=object-detection
36-
providersMapping={ {"hf-inference":{"modelId":"facebook/detr-resnet-50","providerModelId":"facebook/detr-resnet-50"}} }
37-
/>
33+
There are currently no snippet examples for the **object-detection** task, as no providers support it yet.
3834

3935

4036

‎docs/inference-providers/tasks/question-answering.md‎

Lines changed: 4 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -24,6 +24,9 @@ For more details about the `question-answering` task, check out its [dedicated p
2424

2525
### Recommended models
2626

27+
- [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2): A robust baseline model for most question answering domains.
28+
- [distilbert/distilbert-base-cased-distilled-squad](https://huggingface.co/distilbert/distilbert-base-cased-distilled-squad): Small yet robust model that can answer questions.
29+
- [google/tapas-base-finetuned-wtq](https://huggingface.co/google/tapas-base-finetuned-wtq): A special model that can answer questions from tables.
2730

2831
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).
2932

@@ -32,7 +35,7 @@ Explore all available models and find the one that suits you best [here](https:/
3235

3336
<InferenceSnippet
3437
pipeline=question-answering
35-
providersMapping={ {"hf-inference":{"modelId":"uer/roberta-base-chinese-extractive-qa","providerModelId":"uer/roberta-base-chinese-extractive-qa"}} }
38+
providersMapping={ {"hf-inference":{"modelId":"deepset/roberta-base-squad2","providerModelId":"deepset/roberta-base-squad2"}} }
3639
/>
3740

3841

0 commit comments

Comments
 (0)