Upload folder using huggingface_hub
Browse files- README.md +40 -0
- adapter_config.json +33 -0
- adapter_model.safetensors +3 -0
- checkpoint-9676/README.md +202 -0
- checkpoint-9676/adapter_config.json +33 -0
- checkpoint-9676/adapter_model.safetensors +3 -0
- checkpoint-9676/optimizer.pt +3 -0
- checkpoint-9676/pytorch_model.bin +3 -0
- checkpoint-9676/rng_state.pth +3 -0
- checkpoint-9676/scheduler.pt +3 -0
- checkpoint-9676/special_tokens_map.json +24 -0
- checkpoint-9676/tokenizer.json +0 -0
- checkpoint-9676/tokenizer.model +3 -0
- checkpoint-9676/tokenizer_config.json +43 -0
- checkpoint-9676/trainer_state.json +2730 -0
- checkpoint-9676/training_args.bin +3 -0
- handler.py +32 -0
- requirements.txt +2 -0
- runs/Mar21_02-37-23_r-nicolof88-mistral7b-spider-at-188n2lyh-a2f2a-vnlru/events.out.tfevents.1710988652.r-nicolof88-mistral7b-spider-at-188n2lyh-a2f2a-vnlru.98.0 +2 -2
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +43 -0
- training_args.bin +3 -0
- training_params.json +47 -0
README.md
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---
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tags:
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- autotrain
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- text-generation
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widget:
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- text: "I love AutoTrain because "
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license: other
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---
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# Model Trained Using AutoTrain
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This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
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# Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_path = "PATH_TO_THIS_REPO"
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tokenizer = AutoTokenizer.from_pretrained(model_path)
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model = AutoModelForCausalLM.from_pretrained(
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model_path,
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device_map="auto",
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torch_dtype='auto'
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).eval()
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# Prompt content: "hi"
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messages = [
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{"role": "user", "content": "hi"}
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]
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input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
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output_ids = model.generate(input_ids.to('cuda'))
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response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
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# Model response: "Hello! How can I assist you today?"
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print(response)
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```
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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": "mistralai/Mistral-7B-Instruct-v0.2",
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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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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 16,
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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": 64,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"q_proj",
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"down_proj",
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"v_proj",
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"up_proj",
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"k_proj",
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"gate_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:cf35931b3c5aed981d5e1d9a71d0340a4761c5157b8fccf28d16da2b1c080439
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size 671149168
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checkpoint-9676/README.md
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---
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library_name: peft
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base_model: mistralai/Mistral-7B-Instruct-v0.2
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---
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5 |
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|
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# Model Card for Model ID
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7 |
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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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25 |
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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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29 |
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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33 |
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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|
36 |
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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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39 |
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40 |
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### Direct Use
|
41 |
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42 |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
43 |
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|
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[More Information Needed]
|
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|
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### Downstream Use [optional]
|
47 |
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48 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
49 |
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|
50 |
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[More Information Needed]
|
51 |
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|
52 |
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### Out-of-Scope Use
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53 |
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|
54 |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
55 |
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|
56 |
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[More Information Needed]
|
57 |
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|
58 |
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## Bias, Risks, and Limitations
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59 |
+
|
60 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
61 |
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|
62 |
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[More Information Needed]
|
63 |
+
|
64 |
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### Recommendations
|
65 |
+
|
66 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
67 |
+
|
68 |
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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.
|
69 |
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|
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## How to Get Started with the Model
|
71 |
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|
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Use the code below to get started with the model.
|
73 |
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|
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[More Information Needed]
|
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|
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## Training Details
|
77 |
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|
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### Training Data
|
79 |
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|
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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. -->
|
81 |
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|
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[More Information Needed]
|
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|
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### Training Procedure
|
85 |
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|
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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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|
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#### Preprocessing [optional]
|
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[More Information Needed]
|
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|
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|
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#### Training Hyperparameters
|
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|
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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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+
|
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#### Speeds, Sizes, Times [optional]
|
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|
99 |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
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|
101 |
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[More Information Needed]
|
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|
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## Evaluation
|
104 |
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|
105 |
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<!-- This section describes the evaluation protocols and provides the results. -->
|
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|
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### Testing Data, Factors & Metrics
|
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|
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#### Testing Data
|
110 |
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111 |
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<!-- This should link to a Dataset Card if possible. -->
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|
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[More Information Needed]
|
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|
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#### Factors
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|
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
118 |
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|
119 |
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[More Information Needed]
|
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|
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#### Metrics
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|
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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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|
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### Results
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[More Information Needed]
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#### Summary
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132 |
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## Model Examination [optional]
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136 |
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|
137 |
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<!-- Relevant interpretability work for the model goes here -->
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138 |
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|
139 |
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[More Information Needed]
|
140 |
+
|
141 |
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## Environmental Impact
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142 |
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|
143 |
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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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|
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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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|
147 |
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- **Hardware Type:** [More Information Needed]
|
148 |
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- **Hours used:** [More Information Needed]
|
149 |
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- **Cloud Provider:** [More Information Needed]
|
150 |
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- **Compute Region:** [More Information Needed]
|
151 |
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- **Carbon Emitted:** [More Information Needed]
|
152 |
+
|
153 |
+
## Technical Specifications [optional]
|
154 |
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|
155 |
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### Model Architecture and Objective
|
156 |
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|
157 |
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[More Information Needed]
|
158 |
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|
159 |
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### Compute Infrastructure
|
160 |
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|
161 |
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[More Information Needed]
|
162 |
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|
163 |
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#### Hardware
|
164 |
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|
165 |
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[More Information Needed]
|
166 |
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|
167 |
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#### Software
|
168 |
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|
169 |
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[More Information Needed]
|
170 |
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|
171 |
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## Citation [optional]
|
172 |
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|
173 |
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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. -->
|
174 |
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|
175 |
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**BibTeX:**
|
176 |
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|
177 |
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[More Information Needed]
|
178 |
+
|
179 |
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**APA:**
|
180 |
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|
181 |
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[More Information Needed]
|
182 |
+
|
183 |
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## Glossary [optional]
|
184 |
+
|
185 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
186 |
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|
187 |
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[More Information Needed]
|
188 |
+
|
189 |
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## More Information [optional]
|
190 |
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|
191 |
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[More Information Needed]
|
192 |
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|
193 |
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## Model Card Authors [optional]
|
194 |
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|
195 |
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[More Information Needed]
|
196 |
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|
197 |
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## Model Card Contact
|
198 |
+
|
199 |
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[More Information Needed]
|
200 |
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### Framework versions
|
201 |
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|
202 |
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- PEFT 0.9.0
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checkpoint-9676/adapter_config.json
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{
|
2 |
+
"alpha_pattern": {},
|
3 |
+
"auto_mapping": null,
|
4 |
+
"base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.2",
|
5 |
+
"bias": "none",
|
6 |
+
"fan_in_fan_out": false,
|
7 |
+
"inference_mode": true,
|
8 |
+
"init_lora_weights": true,
|
9 |
+
"layers_pattern": null,
|
10 |
+
"layers_to_transform": null,
|
11 |
+
"loftq_config": {},
|
12 |
+
"lora_alpha": 16,
|
13 |
+
"lora_dropout": 0.05,
|
14 |
+
"megatron_config": null,
|
15 |
+
"megatron_core": "megatron.core",
|
16 |
+
"modules_to_save": null,
|
17 |
+
"peft_type": "LORA",
|
18 |
+
"r": 64,
|
19 |
+
"rank_pattern": {},
|
20 |
+
"revision": null,
|
21 |
+
"target_modules": [
|
22 |
+
"q_proj",
|
23 |
+
"down_proj",
|
24 |
+
"v_proj",
|
25 |
+
"up_proj",
|
26 |
+
"k_proj",
|
27 |
+
"gate_proj",
|
28 |
+
"o_proj"
|
29 |
+
],
|
30 |
+
"task_type": "CAUSAL_LM",
|
31 |
+
"use_dora": false,
|
32 |
+
"use_rslora": false
|
33 |
+
}
|
checkpoint-9676/adapter_model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
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|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:cf35931b3c5aed981d5e1d9a71d0340a4761c5157b8fccf28d16da2b1c080439
|
3 |
+
size 671149168
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checkpoint-9676/optimizer.pt
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 1342555602
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checkpoint-9676/pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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size 888
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checkpoint-9676/rng_state.pth
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 14244
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checkpoint-9676/scheduler.pt
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 1064
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checkpoint-9676/special_tokens_map.json
ADDED
@@ -0,0 +1,24 @@
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{
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|
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|
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|
checkpoint-9676/tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
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checkpoint-9676/tokenizer.model
ADDED
@@ -0,0 +1,3 @@
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1 |
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version https://git-lfs.github.com/spec/v1
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size 493443
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checkpoint-9676/tokenizer_config.json
ADDED
@@ -0,0 +1,43 @@
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|
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|
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|
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},
|
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"additional_special_tokens": [],
|
31 |
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"bos_token": "<s>",
|
32 |
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"chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
|
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|
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"eos_token": "</s>",
|
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|
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|
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|
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|
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|
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|
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|
42 |
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"use_default_system_prompt": false
|
43 |
+
}
|
checkpoint-9676/trainer_state.json
ADDED
@@ -0,0 +1,2730 @@
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checkpoint-9676/training_args.bin
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version https://git-lfs.github.com/spec/v1
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size 4984
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handler.py
ADDED
@@ -0,0 +1,32 @@
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|
1 |
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from typing import Dict, List, Any
|
2 |
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
|
3 |
+
import torch
|
4 |
+
from peft import PeftModel
|
5 |
+
import json
|
6 |
+
import os
|
7 |
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|
8 |
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|
9 |
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class EndpointHandler():
|
10 |
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def __init__(self, path=""):
|
11 |
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base_model_path = json.load(open(os.path.join(path, "training_params.json")))["model"]
|
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model = AutoModelForCausalLM.from_pretrained(
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base_model_path,
|
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torch_dtype=torch.float16,
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low_cpu_mem_usage=True,
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trust_remote_code=True,
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device_map="auto",
|
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)
|
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tokenizer = AutoTokenizer.from_pretrained(path, trust_remote_code=True)
|
20 |
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model.resize_token_embeddings(len(tokenizer))
|
21 |
+
model = PeftModel.from_pretrained(model, path)
|
22 |
+
model = model.merge_and_unload()
|
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+
self.pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
|
24 |
+
|
25 |
+
def __call__(self, data: Any) -> List[List[Dict[str, float]]]:
|
26 |
+
inputs = data.pop("inputs", data)
|
27 |
+
parameters = data.pop("parameters", None)
|
28 |
+
if parameters is not None:
|
29 |
+
prediction = self.pipeline(inputs, **parameters)
|
30 |
+
else:
|
31 |
+
prediction = self.pipeline(inputs)
|
32 |
+
return prediction
|
requirements.txt
ADDED
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
1 |
+
peft==0.9.0
|
2 |
+
transformers==4.38.2
|
runs/Mar21_02-37-23_r-nicolof88-mistral7b-spider-at-188n2lyh-a2f2a-vnlru/events.out.tfevents.1710988652.r-nicolof88-mistral7b-spider-at-188n2lyh-a2f2a-vnlru.98.0
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special_tokens_map.json
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}
|
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}
|
tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
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tokenizer.model
ADDED
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tokenizer_config.json
ADDED
@@ -0,0 +1,43 @@
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},
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"additional_special_tokens": [],
|
31 |
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"bos_token": "<s>",
|
32 |
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"chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
|
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|
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|
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"unk_token": "<unk>",
|
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"use_default_system_prompt": false
|
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}
|
training_args.bin
ADDED
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training_params.json
ADDED
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{
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|
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|
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|
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|
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|
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"username": "nicolof88"
|
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}
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