Isaak Carter Augustus
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README.md
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library_name: transformers
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# Model
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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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library_name: transformers
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base_model: mistralai/Mistral-7B-Instruct-v0.3
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# Model card of JOSIExMistral-7B-Instruct-v0.2
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## This is my Token customized mistralai/Mistral-7B-Instruct-v0.2 model
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[Origional Model](https://huggingface.co/mistralai/mistralai/Mistral-7B-Instruct-v0.3)
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This is based on mistralai/Mistral-7B-Instruct-v0.2 model with added custom special Tokens. This wil most likely be my next Model, trained on my own Dataset.
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[--> GGUF Quants <--](https://huggingface.co/mradermacher/Isaak-Carter/JOSIExMistral-7B-v0.32)
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<br>
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### New added Special Tokens
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```text
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'<|functions|>',
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'<|system|>',
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'<|gökdeniz|>',
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'<|user|>',
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'<|josie|>',
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'<|assistant|>',
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'<|function_call|>',
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'<|function_response|>',
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'<|image|>',
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'<|long_term_memory|>',
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'<|short_term_memory|>',
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'<|home_state|>',
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'<|current_states|>',
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'<|context|>',
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'<|im_start|>',
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'<|im_end|>'
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```
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<br>
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### New BOS and EOS Tokens
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```text
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BOS = '<|startoftext|>'
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EOS = '<|endoftext|>'
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```
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<br>
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## Model Architecture:
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```text
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MistralForCausalLM(
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(model): MistralModel(
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(embed_tokens): Embedding(32018, 4096)
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(layers): ModuleList(
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(0-31): 32 x MistralDecoderLayer(
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(self_attn): MistralSdpaAttention(
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(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
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(k_proj): Linear(in_features=4096, out_features=1024, bias=False)
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(v_proj): Linear(in_features=4096, out_features=1024, bias=False)
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(o_proj): Linear(in_features=4096, out_features=4096, bias=False)
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(rotary_emb): MistralRotaryEmbedding()
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)
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(mlp): MistralMLP(
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(gate_proj): Linear(in_features=4096, out_features=14336, bias=False)
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(up_proj): Linear(in_features=4096, out_features=14336, bias=False)
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(down_proj): Linear(in_features=14336, out_features=4096, bias=False)
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(act_fn): SiLU()
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)
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(input_layernorm): MistralRMSNorm()
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(post_attention_layernorm): MistralRMSNorm()
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)
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)
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(norm): MistralRMSNorm()
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)
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(lm_head): Linear(in_features=4096, out_features=32018, bias=False)
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)
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```
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