Upload WhisperForConditionalGeneration

README.md

@@ -1,148 +1,199 @@
 ---
-license: apache-2.0
 library_name: transformers
-pipeline_tag: automatic-speech-recognition
-tags:
-- asr
-- Pytorch
-- pruned
-- audio
-- automatic-speech-recognition
-language:
-- en
-- zh
-- de
-- es
-- ru
-- ko
-- fr
-- ja
-- pt
-- tr
-- pl
-- ca
-- nl
-- ar
-- sv
-- it
-- id
-- hi
-- fi
-- vi
-- he
-- uk
-- el
-- ms
-- cs
-- ro
-- da
-- hu
-- ta
-- 'no'
-- th
-- ur
-- hr
-- bg
-- lt
-- la
-- mi
-- ml
-- cy
-- sk
-- te
-- fa
-- lv
-- bn
-- sr
-- az
-- sl
-- kn
-- et
-- mk
-- br
-- eu
-- is
-- hy
-- ne
-- mn
-- bs
-- kk
-- sq
-- sw
-- gl
-- mr
-- pa
-- si
-- km
-- sn
-- yo
-- so
-- af
-- oc
-- ka
-- be
-- tg
-- sd
-- gu
-- am
-- yi
-- lo
-- uz
-- fo
-- ht
-- ps
-- tk
-- nn
-- mt
-- sa
-- lb
-- my
-- bo
-- tl
-- mg
-- as
-- tt
-- haw
-- ln
-- ha
-- ba
-- jw
-- su
-base_model:
-- openai/whisper-large-v3-turbo
+tags: []
 ---
 
-# Whisper-large-v3-turbo-no-numbers
+# Model Card for Model ID
 
-## Model info
-This is a version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) model without number tokens (token ids corresponding to numbers are excluded).
-NO fine-tuning was used.
+<!-- Provide a quick summary of what the model is/does. -->
 
-Phrases with spoken numbers will be transcribed with numbers as words.
 
-Example: Instead of "25" this model will transcribe phrase as "twenty five".
 
-## Usage
-Model can be used as an original whisper:
+## Model Details
 
-```python
->>> from transformers import WhisperProcessor, WhisperForConditionalGeneration
->>> import torchaudio
+### Model Description
 
->>> # load audio
->>> wav, sr = torchaudio.load("audio.wav")
+<!-- Provide a longer summary of what this model is. -->
 
->>> # load model and processor
->>> processor = WhisperProcessor.from_pretrained("waveletdeboshir/whisper-large-v3-turbo-no-numbers")
->>> model = WhisperForConditionalGeneration.from_pretrained("waveletdeboshir/whisper-large-v3-turbo-no-numbers")
+This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
 
->>> input_features = processor(wav[0], sampling_rate=sr, return_tensors="pt").input_features 
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
 
->>> # generate token ids
->>> predicted_ids = model.generate(input_features)
->>> # decode token ids to text
->>> transcription = processor.batch_decode(predicted_ids, skip_special_tokens=False)
-["<|startoftranscript|><|en|><|transcribe|><|notimestamps|> Twenty seven years. <|endoftext|>"]
+### Model Sources [optional]
 
-```
-The context tokens can be removed from the start of the transcription by setting `skip_special_tokens=True`.
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]

config.json

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+{
+  "_name_or_path": "./models/whisper-large-v3-turbo-no-numbers",
+  "activation_dropout": 0.0,
+  "activation_function": "gelu",
+  "apply_spec_augment": false,
+  "architectures": [
+    "WhisperForConditionalGeneration"
+  ],
+  "attention_dropout": 0.0,
+  "begin_suppress_tokens": [
+    210,
+    49838
+  ],
+  "bos_token_id": 49839,
+  "classifier_proj_size": 256,
+  "d_model": 1280,
+  "decoder_attention_heads": 20,
+  "decoder_ffn_dim": 5120,
+  "decoder_layerdrop": 0.0,
+  "decoder_layers": 4,
+  "decoder_start_token_id": 49840,
+  "dropout": 0.0,
+  "encoder_attention_heads": 20,
+  "encoder_ffn_dim": 5120,
+  "encoder_layerdrop": 0.0,
+  "encoder_layers": 32,
+  "eos_token_id": 49839,
+  "forced_decoder_ids": [
+    [
+      1,
+      49841
+    ],
+    [
+      2,
+      49941
+    ],
+    [
+      3,
+      49945
+    ]
+  ],
+  "init_std": 0.02,
+  "is_encoder_decoder": true,
+  "mask_feature_length": 10,
+  "mask_feature_min_masks": 0,
+  "mask_feature_prob": 0.0,
+  "mask_time_length": 10,
+  "mask_time_min_masks": 2,
+  "mask_time_prob": 0.05,
+  "max_source_positions": 1500,
+  "max_target_positions": 448,
+  "median_filter_width": 7,
+  "model_type": "whisper",
+  "num_hidden_layers": 32,
+  "num_mel_bins": 128,
+  "pad_token_id": 49839,
+  "scale_embedding": false,
+  "suppress_tokens": [],
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.0",
+  "use_cache": true,
+  "use_weighted_layer_sum": false,
+  "vocab_size": 51447
+}

generation_config.json

@@ -0,0 +1,160 @@
+{
+  "alignment_heads": [
+    [
+      2,
+      4
+    ],
+    [
+      2,
+      11
+    ],
+    [
+      3,
+      3
+    ],
+    [
+      3,
+      6
+    ],
+    [
+      3,
+      11
+    ],
+    [
+      3,
+      14
+    ]
+  ],
+  "begin_suppress_tokens": [
+    210,
+    49839
+  ],
+  "bos_token_id": 49839,
+  "decoder_start_token_id": 49840,
+  "eos_token_id": 49839,
+  "forced_decoder_ids": [
+    [
+      1,
+      null
+    ],
+    [
+      2,
+      49941
+    ]
+  ],
+  "is_multilingual": true,
+  "lang_to_id": {
+    "<|af|>": 49909,
+    "<|am|>": 49916,
+    "<|ar|>": 49854,
+    "<|as|>": 49932,
+    "<|az|>": 49886,
+    "<|ba|>": 49937,
+    "<|be|>": 49912,
+    "<|bg|>": 49874,
+    "<|bn|>": 49884,
+    "<|bo|>": 49929,
+    "<|br|>": 49891,
+    "<|bs|>": 49897,
+    "<|ca|>": 49852,
+    "<|cs|>": 49865,
+    "<|cy|>": 49879,
+    "<|da|>": 49867,
+    "<|de|>": 49843,
+    "<|el|>": 49863,
+    "<|en|>": 49841,
+    "<|es|>": 49844,
+    "<|et|>": 49889,
+    "<|eu|>": 49892,
+    "<|fa|>": 49882,
+    "<|fi|>": 49859,
+    "<|fo|>": 49920,
+    "<|fr|>": 49847,
+    "<|gl|>": 49901,
+    "<|gu|>": 49915,
+    "<|haw|>": 49934,
+    "<|ha|>": 49936,
+    "<|he|>": 49861,
+    "<|hi|>": 49858,
+    "<|hr|>": 49873,
+    "<|ht|>": 49921,
+    "<|hu|>": 49868,
+    "<|hy|>": 49894,
+    "<|id|>": 49857,
+    "<|is|>": 49893,
+    "<|it|>": 49856,
+    "<|ja|>": 49848,
+    "<|jw|>": 49938,
+    "<|ka|>": 49911,
+    "<|kk|>": 49898,
+    "<|km|>": 49905,
+    "<|kn|>": 49888,
+    "<|ko|>": 49846,
+    "<|la|>": 49876,
+    "<|lb|>": 49927,
+    "<|ln|>": 49935,
+    "<|lo|>": 49918,
+    "<|lt|>": 49875,
+    "<|lv|>": 49883,
+    "<|mg|>": 49931,
+    "<|mi|>": 49877,
+    "<|mk|>": 49890,
+    "<|ml|>": 49878,
+    "<|mn|>": 49896,
+    "<|mr|>": 49902,
+    "<|ms|>": 49864,
+    "<|mt|>": 49925,
+    "<|my|>": 49928,
+    "<|ne|>": 49895,
+    "<|nl|>": 49853,
+    "<|nn|>": 49924,
+    "<|no|>": 49870,
+    "<|oc|>": 49910,
+    "<|pa|>": 49903,
+    "<|pl|>": 49851,
+    "<|ps|>": 49922,
+    "<|pt|>": 49849,
+    "<|ro|>": 49866,
+    "<|ru|>": 49845,
+    "<|sa|>": 49926,
+    "<|sd|>": 49914,
+    "<|si|>": 49904,
+    "<|sk|>": 49880,
+    "<|sl|>": 49887,
+    "<|sn|>": 49906,
+    "<|so|>": 49908,
+    "<|sq|>": 49899,
+    "<|sr|>": 49885,
+    "<|su|>": 49939,
+    "<|sv|>": 49855,
+    "<|sw|>": 49900,
+    "<|ta|>": 49869,
+    "<|te|>": 49881,
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+    "<|th|>": 49871,
+    "<|tk|>": 49923,
+    "<|tl|>": 49930,
+    "<|tr|>": 49850,
+    "<|tt|>": 49933,
+    "<|uk|>": 49862,
+    "<|ur|>": 49872,
+    "<|uz|>": 49919,
+    "<|vi|>": 49860,
+    "<|yi|>": 49917,
+    "<|yo|>": 49907,
+    "<|yue|>": 49940,
+    "<|zh|>": 49842
+  },
+  "max_initial_timestamp_index": 50,
+  "max_length": 448,
+  "no_timestamps_token_id": 49946,
+  "pad_token_id": 49839,
+  "prev_sot_token_id": 49944,
+  "return_timestamps": false,
+  "suppress_tokens": [],
+  "task_to_id": {
+    "transcribe": 49942,
+    "translate": 49941
+  },
+  "transformers_version": "4.44.0"
+}

model.safetensors

@@ -0,0 +1,3 @@
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+size 3233436128