first init
Browse files- README.md +202 -0
- adapter_config.json +34 -0
- adapter_model.safetensors +3 -0
- clip/all_results.json +13 -0
- clip/config.json +31 -0
- clip/eval_results.json +8 -0
- clip/merges.txt +0 -0
- clip/model.safetensors +3 -0
- clip/preprocessor_config.json +44 -0
- clip/special_tokens_map.json +30 -0
- clip/tokenizer_config.json +31 -0
- clip/train_results.json +8 -0
- clip/trainer_state.json +286 -0
- clip/training_args.bin +3 -0
- clip/vocab.json +0 -0
- config.json +44 -0
- non_lora_trainables.bin +3 -0
- trainer_state.json +0 -0
README.md
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---
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library_name: peft
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base_model: /home/yfliu/data/code/rl_with_clip/cache/model/vicuna-7b-v1.5
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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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- **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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### Framework versions
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- PEFT 0.11.1
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "vicuna-7b-v1.5",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 256,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 128,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"gate_proj",
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"v_proj",
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"up_proj",
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"down_proj",
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"k_proj",
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"q_proj",
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"o_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:88d850a919a746f5a6b9e0bd50f7552c79800b3a83e339fc7d300248bcccc57f
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size 639692768
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clip/all_results.json
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{
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"epoch": 10.0,
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"eval_accuracy": 0.9,
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"eval_loss": 0.9871606230735779,
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"eval_runtime": 78.3792,
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"eval_samples_per_second": 12.631,
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"eval_steps_per_second": 0.051,
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"total_flos": 8.059090729915764e+17,
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"train_loss": 0.06507109994963398,
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"train_runtime": 16858.8681,
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"train_samples_per_second": 9.491,
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"train_steps_per_second": 0.678
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}
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clip/config.json
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{
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"_name_or_path": "../cache/model/clip-vit-large-patch14-336",
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"architectures": [
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"CLIPModel"
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],
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"initializer_factor": 1.0,
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"logit_scale_init_value": 2.6592,
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"model_type": "clip",
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"projection_dim": 768,
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"text_config": {
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"dropout": 0.0,
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"hidden_size": 768,
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"intermediate_size": 3072,
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"model_type": "clip_text_model",
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"num_attention_heads": 12,
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"projection_dim": 768
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},
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"torch_dtype": "float32",
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"transformers_version": "4.41.2",
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"vision_config": {
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"dropout": 0.0,
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"hidden_size": 1024,
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"image_size": 336,
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"intermediate_size": 4096,
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"model_type": "clip_vision_model",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"patch_size": 14,
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"projection_dim": 768
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}
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}
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clip/eval_results.json
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{
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"epoch": 10.0,
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"eval_accuracy": 0.9,
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"eval_loss": 0.9871606230735779,
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"eval_runtime": 78.3792,
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"eval_samples_per_second": 12.631,
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"eval_steps_per_second": 0.051
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}
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clip/merges.txt
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The diff for this file is too large to render.
See raw diff
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clip/model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:dcef3e68ead1045defeb330dcd34ad5d1f47716de003c4048708f265670e7ae5
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size 1711848436
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clip/preprocessor_config.json
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{
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"_valid_processor_keys": [
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"images",
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"do_resize",
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"size",
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"resample",
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"do_center_crop",
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"crop_size",
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"do_rescale",
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"rescale_factor",
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"do_normalize",
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"image_mean",
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"image_std",
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"do_convert_rgb",
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"return_tensors",
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"data_format",
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"input_data_format"
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18 |
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