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README.md

@@ -1,39 +1,203 @@
 ---
 library_name: peft
-widget:
-- text: >-
-    Claire makes a 3 egg omelet every morning for breakfast. How many dozens of
-    eggs will she eat in 4 weeks?
-  example_title: Solve math
-pipeline_tag: text-generation
-license: apache-2.0
-datasets:
-- gsm8k
-language:
-- en
+base_model: HuggingFaceH4/zephyr-7b-beta
 ---
-## Usage 
 
-```python
-from peft import PeftModel, PeftConfig
-from transformers import AutoModelForCausalLM
+# Model Card for Model ID
 
-config = PeftConfig.from_pretrained("mwitiderrick/zephyr-7b-beta-gsm8k")
-model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/zephyr-7b-beta")
-model = PeftModel.from_pretrained(model, "mwitiderrick/zephyr-7b-beta-gsm8k")
+<!-- Provide a quick summary of what the model is/does. -->
 
-prompt = "James decides to run 3 sprints 3 times a week. He runs 60 meters each sprint. How many total meters does he run a week?"
-pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=200)
-result = pipe(f"<s>[INST] {prompt} [/INST]")
-print(result[0]['generated_text'])
 
-"""
-<s>[INST] Claire makes a 3 egg omelet every morning for breakfast. How many dozens of eggs will she eat in 4 weeks? [/INST]  She eats 3*7=<<3*7=21>>21 eggs a week
-So she eats 21*4=<<21*4=84>>84 eggs in 4 weeks
-That means she eats 84/12=<<84/12=7>>7 dozen eggs
-"""
 
-```
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [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]
+
+### Model Sources [optional]
+
+<!-- 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 Data 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 Data 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]
+
+
 ## Training procedure
 
 
@@ -49,6 +213,13 @@ The following `bitsandbytes` quantization config was used during training:
 - bnb_4bit_use_double_quant: False
 - bnb_4bit_compute_dtype: bfloat16
 
+### Framework versions
+
+
+- PEFT 0.6.0
+## Training procedure
+
+
 The following `bitsandbytes` quantization config was used during training:
 - quant_method: bitsandbytes
 - load_in_8bit: False
@@ -60,8 +231,8 @@ The following `bitsandbytes` quantization config was used during training:
 - bnb_4bit_quant_type: nf4
 - bnb_4bit_use_double_quant: False
 - bnb_4bit_compute_dtype: bfloat16
+
 ### Framework versions
 
-- PEFT 0.5.0
 
-- PEFT 0.5.0
+- PEFT 0.6.0

adapter_config.json

@@ -1,4 +1,5 @@
 {
+  "alpha_pattern": {},
   "auto_mapping": null,
   "base_model_name_or_path": "HuggingFaceH4/zephyr-7b-beta",
   "bias": "none",
@@ -12,13 +13,14 @@
   "modules_to_save": null,
   "peft_type": "LORA",
   "r": 64,
+  "rank_pattern": {},
   "revision": null,
   "target_modules": [
     "q_proj",
-    "k_proj",
-    "v_proj",
+    "gate_proj",
     "o_proj",
-    "gate_proj"
+    "k_proj",
+    "v_proj"
   ],
   "task_type": "CAUSAL_LM"
 }

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6f3d022034edd4b71a0865c6672a142cdc11c85b73c1460e44d3150ef9a9da7a
+size 369142184