huashiyiqike
commited on
Commit
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Parent(s):
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Upload 9 files
Browse files- README.md +186 -1
- config.json +32 -0
- huggingface-metadata.txt +6 -0
- merges.txt +0 -0
- model.safetensors +3 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer_config.json +34 -0
- vocab.json +0 -0
README.md
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---
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license:
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---
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---
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license: cc-by-nc-sa-4.0
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datasets:
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- tatsu-lab/alpaca
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- the_pile
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---
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# Model Card for Cerebras 111M Dollyfied.
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This is a finetuned model of Cerebras 111M model. using DataBricksLabs Dolly Framework
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## Model Details
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### Model Description
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This is a finetuned version of cerebras' 111million paramater model that has been trained to follow instructions.
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It was accomplished using DataBricks Dolly training tools and the alpaca dataset, and was trained for 2 epochs.
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- **Developed by:** Finetuned by Corianas (me) using open source tools
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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):** EN
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- **License:** cc-by-nc-4.0
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- **Finetuned from model:** https://huggingface.co/cerebras/Cerebras-GPT-111m
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- **Finetuned using:** https://www.databricks.com/blog/2023/03/24/hello-dolly-democratizing-magic-chatgpt-open-models.html
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## Uses
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This is a simple GPT chatbot that has been finetuned to understand instructions.
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Its knowledge about facts about the world is should be considered suspect at best.
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### Direct Use
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If you have a use you put it to, Please let me know.
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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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Any form of use where any form of accuracy is needed.
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FOR THE LOVE OF GOD DO NOT FOLLOW MEDICAL ADVICE FROM THIS.
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or financial advice.
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[More Information Needed]
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## Bias, Risks, and Limitations
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Limitations... Yes, I am sure there are so so many.
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[More Information Needed]
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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 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. -->
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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 Data 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:** 8xA100s (accomplished while I was downloading the model I was actually training.)
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- **Minutes used:** 7.5
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- **Cloud Provider:** LambdaGPU
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- **Compute Region:** USA
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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": "cerebras/Cerebras-GPT-111M",
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"activation_function": "gelu",
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"architectures": [
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"GPT2LMHeadModel"
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],
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"attn_pdrop": 0.0,
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"bos_token_id": 50256,
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"embd_pdrop": 0.0,
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"eos_token_id": 50256,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"model_type": "gpt2",
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"n_embd": 768,
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"n_head": 12,
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"n_inner": 3072,
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"n_layer": 10,
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"n_positions": 2048,
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"reorder_and_upcast_attn": false,
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"resid_pdrop": 0.0,
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"scale_attn_by_inverse_layer_idx": false,
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"scale_attn_weights": true,
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"summary_activation": null,
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"summary_first_dropout": 0.1,
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.25.1",
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"use_cache": false,
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"vocab_size": 50257
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}
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huggingface-metadata.txt
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url: https://huggingface.co/Corianas/111m
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branch: main
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download date: 2023-08-22 16:42:49
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sha256sum:
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9d8e0e14dee78548497a1460e94174a59137334a7b5543e0714f7e4179631d47 model.safetensors
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e11b2e73d6ea7b3f9a0d11cc81db9fcd618c517288103d47fe842e517bf9aaa5 pytorch_model.bin
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merges.txt
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9d8e0e14dee78548497a1460e94174a59137334a7b5543e0714f7e4179631d47
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size 264058626
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "<|endoftext|>",
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"unk_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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tokenizer_config.json
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{
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"add_bos_token": false,
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"add_prefix_space": false,
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"bos_token": {
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"__type": "AddedToken",
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"__type": "AddedToken",
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"errors": "replace",
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"model_max_length": 1000000000000000019884624838656,
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"name_or_path": "cerebras/Cerebras-GPT-111M",
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"pad_token": null,
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"special_tokens_map_file": null,
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"tokenizer_class": "GPT2Tokenizer",
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"unk_token": {
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"__type": "AddedToken",
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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vocab.json
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