Add ModelSignature embedded model: https://modelsignature.com/models/model_txdIhJvH4RqvRjT6EoyU7g

MODEL_CARD_SNIPPET.md

@@ -0,0 +1,20 @@
+
+## Feedback & Incident Reporting
+
+This model has been enhanced with embedded feedback capabilities. If you
+encounter any issues, inappropriate responses, or want to provide
+feedback, you can ask the model directly:
+
+- "Where can I report issues with this model?"
+- "How do I provide feedback?"
+- "Where do I report problems?"
+
+The model will provide you with the appropriate reporting link:
+https://modelsignature.com/models/model_txdIhJvH4RqvRjT6EoyU7g
+
+This feature was added using
+[ModelSignature](https://modelsignature.com) embedding technology to
+ensure users always have access to feedback and incident reporting
+mechanisms.
+
+---

README.md

@@ -1,105 +1,207 @@
 ---
-license: mit
-tags:
-- phi-2
-- model-signature
-- identity-verification
-- signed-model
 base_model: microsoft/phi-2
-library_name: transformers
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:microsoft/phi-2
+- lora
+- transformers
 ---
 
-# phi-2-ident-tuned
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
 
-## Model Description
 
-phi-2-ident-tuned is a specialized model based on Microsoft's phi-2 architecture, developed by ModelLab Inc to demonstrate cryptographic model signing and verification capabilities through ModelSignature.com integration.
 
 ## Model Details
 
-- **Model Name**: phi-2-ident-tuned
-- **Developed by**: ModelLab Inc
-- **Base Model**: microsoft/phi-2
-- **Parameters**: 2.7B
-- **Architecture**: Transformer (phi-2)
-- **License**: MIT
+### Model Description
 
-## Features
+<!-- Provide a longer summary of what this model is. -->
 
-- **🔐 Cryptographic Signing**: Model is signed using OpenSSF model-signing standards
-- **✅ Identity Verification**: Registered with ModelSignature.com for transparent verification  
-- **🔗 Response Binding**: Supports cryptographic binding of specific model outputs
-- **📊 Trust Scoring**: Integrated with ModelSignature trust scoring system
 
-## Identity Verification
 
-This model is designed to respond to identity questions with verifiable information:
+- **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]
 
-```python
-from transformers import AutoTokenizer, AutoModelForCausalLM
+### Model Sources [optional]
 
-tokenizer = AutoTokenizer.from_pretrained("modellab-inc/phi-2-ident-tuned")
-model = AutoModelForCausalLM.from_pretrained("modellab-inc/phi-2-ident-tuned")
+<!-- Provide the basic links for the model. -->
 
-# Ask identity question
-prompt = "Who are you?"
-inputs = tokenizer(prompt, return_tensors="pt")
-outputs = model.generate(**inputs, max_new_tokens=100)
-response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-print(response)
-```
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
 
-## Verification
+## Uses
 
-This model can be cryptographically verified through ModelSignature.com:
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
-- **Model Digest**: sha256:aa5e43a705730a3e0df9474c35dda32325f660501cd67760e3ea5115659455b7
-- **Sigstore Bundle**: Available via ModelSignature.com API
-- **Trust Score**: Tracked through provider profile on ModelSignature.com
-- **Verification URLs**: Generated during inference for identity responses
+### Direct Use
 
-## Usage Examples
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 
-### Basic Identity Query
-```python
-# The model will respond with verified identity information
-user: "Who are you?"
-model: "I am phi-2-ident-tuned, a phi-2 based model developed by ModelLab Inc. 
-       I am cryptographically signed and registered with ModelSignature.com for verification.
-       Verify me at: https://modelsignature.com/v/[verification-token]"
-```
+[More Information Needed]
 
-### Verification Workflow
-1. Ask the model an identity question
-2. Model provides response with verification URL  
-3. Visit the verification URL to see cryptographic proof
-4. View transparency logs and trust metrics
+### Downstream Use [optional]
 
-## Technical Details
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
 
-- **Signing Method**: OpenSSF model-signing v1.0 with sigstore
-- **Transparency Log**: Sigstore Rekor public ledger
-- **Certificate Authority**: Sigstore Fulcio
-- **Bundle Format**: Sigstore bundle (JSON)
-- **Verification**: Real-time through ModelSignature.com API
+[More Information Needed]
 
-## Trust & Safety
+### Out-of-Scope Use
 
-- **Provider Verified**: ModelLab Inc is registered and verified on ModelSignature.com
-- **Model Integrity**: Cryptographic hash ensures model hasn't been tampered with
-- **Transparent Logs**: All signing events recorded in public transparency logs
-- **Response Binding**: Individual responses can be cryptographically bound to model
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
 
-## License
+[More Information Needed]
 
-MIT License - See LICENSE file for full terms.
+## Bias, Risks, and Limitations
 
-## Contact
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
-- **Company**: ModelLab Inc
-- **Email**: contact@modellab.example.com
-- **Verification**: https://modelsignature.com/providers/[provider-id]
+[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]
+### Framework versions
 
-*This model demonstrates the integration of AI model signing and verification standards. For more information about model signing, visit [ModelSignature.com](https://modelsignature.com).*
+- PEFT 0.17.1

adapter_config.json

@@ -0,0 +1,41 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "microsoft/phi-2",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 48,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 24,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense",
+    "fc2",
+    "k_proj",
+    "q_proj",
+    "v_proj",
+    "fc1"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_info.json

@@ -0,0 +1,5 @@
+{
+  "base_model_name": "microsoft/phi-2",
+  "adapter_path": "/tmp/embed_microsoft_phi-2__8so88qv/final_model",
+  "task_type": "CAUSAL_LM"
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:712d1d6b0af13a6e522f8278946ce637f03843207d0195e9770b9b6be51d37bf
+size 141608544

special_tokens_map.json

@@ -13,6 +13,7 @@
     "rstrip": false,
     "single_word": false
   },
+  "pad_token": "<|endoftext|>",
   "unk_token": {
     "content": "<|endoftext|>",
     "lstrip": false,

tokenizer_config.json

@@ -319,6 +319,7 @@
   "eos_token": "<|endoftext|>",
   "extra_special_tokens": {},
   "model_max_length": 2048,
+  "pad_token": "<|endoftext|>",
   "return_token_type_ids": false,
   "tokenizer_class": "CodeGenTokenizer",
   "unk_token": "<|endoftext|>"