Upload LlavaOnevisionForConditionalGeneration
Browse files- README.md +199 -0
- config.json +209 -0
- generation_config.json +6 -0
- model-00001-of-00002.safetensors +3 -0
- model-00002-of-00002.safetensors +3 -0
- model.safetensors.index.json +0 -0
README.md
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---
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library_name: transformers
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tags: []
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- 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. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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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).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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config.json
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{
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"_name_or_path": "llava-hf/llava-onevision-qwen2-7b-ov-hf",
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"architectures": [
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"LlavaOnevisionForConditionalGeneration"
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],
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"ignore_index": -100,
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"image_grid_pinpoints": [
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"image_token_index": 151646,
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"model_type": "llava_onevision",
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"projector_hidden_act": "gelu",
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"quantization_config": {
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"_load_in_4bit": true,
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"_load_in_8bit": false,
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"bnb_4bit_compute_dtype": "float16",
|
160 |
+
"bnb_4bit_quant_storage": "uint8",
|
161 |
+
"bnb_4bit_quant_type": "nf4",
|
162 |
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"bnb_4bit_use_double_quant": false,
|
163 |
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"llm_int8_enable_fp32_cpu_offload": false,
|
164 |
+
"llm_int8_has_fp16_weight": false,
|
165 |
+
"llm_int8_skip_modules": [
|
166 |
+
"lm_head",
|
167 |
+
"vision_tower"
|
168 |
+
],
|
169 |
+
"llm_int8_threshold": 6.0,
|
170 |
+
"load_in_4bit": true,
|
171 |
+
"load_in_8bit": false,
|
172 |
+
"quant_method": "bitsandbytes"
|
173 |
+
},
|
174 |
+
"text_config": {
|
175 |
+
"_name_or_path": "Qwen/Qwen2-7B-Instruct",
|
176 |
+
"architectures": [
|
177 |
+
"Qwen2ForCausalLM"
|
178 |
+
],
|
179 |
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"bos_token_id": 151643,
|
180 |
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"eos_token_id": 151645,
|
181 |
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"hidden_size": 3584,
|
182 |
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"intermediate_size": 18944,
|
183 |
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"model_type": "qwen2",
|
184 |
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|
185 |
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"num_hidden_layers": 28,
|
186 |
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|
187 |
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"rope_theta": 1000000.0,
|
188 |
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"torch_dtype": "bfloat16",
|
189 |
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"vocab_size": 152128
|
190 |
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},
|
191 |
+
"tie_word_embeddings": false,
|
192 |
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"torch_dtype": "float16",
|
193 |
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"transformers_version": "4.45.1",
|
194 |
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"use_image_newline_parameter": true,
|
195 |
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"video_token_index": 151647,
|
196 |
+
"vision_aspect_ratio": "anyres_max_9",
|
197 |
+
"vision_config": {
|
198 |
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"hidden_size": 1152,
|
199 |
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"image_size": 384,
|
200 |
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"intermediate_size": 4304,
|
201 |
+
"model_type": "siglip_vision_model",
|
202 |
+
"num_attention_heads": 16,
|
203 |
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"num_hidden_layers": 26,
|
204 |
+
"patch_size": 14,
|
205 |
+
"vision_use_head": false
|
206 |
+
},
|
207 |
+
"vision_feature_layer": -1,
|
208 |
+
"vision_feature_select_strategy": "full"
|
209 |
+
}
|
generation_config.json
ADDED
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_from_model_config": true,
|
3 |
+
"bos_token_id": 151643,
|
4 |
+
"eos_token_id": 151645,
|
5 |
+
"transformers_version": "4.45.1"
|
6 |
+
}
|
model-00001-of-00002.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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2 |
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oid sha256:87bdc1556812a32172f7976b78c10dd437c89fb75296954f0e0f0cbc03316582
|
3 |
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size 4999944606
|
model-00002-of-00002.safetensors
ADDED
@@ -0,0 +1,3 @@
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|
|
|
|
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|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:5a2cf6c170fbb4635e705eb7bb11d01887f823b4e985642f80a4d0cca3f29228
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size 1657380820
|
model.safetensors.index.json
ADDED
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|
|