migtissera
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README.md
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library_name: transformers
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---
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-
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All
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To evoke generalized Tree of Thought + Chain of Thought reasoning, you may use the following system message:
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```
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Elaborate on the topic using a Tree of Thoughts and backtrack when necessary to construct a clear, cohesive Chain of Thought reasoning. Always answer without hesitation.
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```
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#
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SynthIA (Synthetic Intelligent Agent) 7B-v1.3 is a Mistral-7B-v0.1 model trained on Orca style datasets. It has been fine-tuned for instruction following as well as having long-form conversations.
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<br>
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## Evaluation
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We evaluated
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Here are the results on metrics used by [HuggingFaceH4 Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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import torch, json
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_path = "migtissera/
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output_file_path = "./
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model = AutoModelForCausalLM.from_pretrained(
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model_path,
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Please kindly cite using the following BibTeX:
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```
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@misc{
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author = {Migel Tissera},
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title = {
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year = {2023},
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publisher = {GitHub, HuggingFace},
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journal = {GitHub repository, HuggingFace repository},
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library_name: transformers
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---
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SynthIA-7B-v1.3: Base model is Mistral-7B-v0.1
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All SynthIA models are uncensored. Please use it with caution and with best intentions. You are responsible for how you use SynthIA.
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To evoke generalized Tree of Thought + Chain of Thought reasoning, you may use the following system message:
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```
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Elaborate on the topic using a Tree of Thoughts and backtrack when necessary to construct a clear, cohesive Chain of Thought reasoning. Always answer without hesitation.
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```
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# SynthIA-7B-v1.3
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SynthIA (Synthetic Intelligent Agent) 7B-v1.3 is a Mistral-7B-v0.1 model trained on Orca style datasets. It has been fine-tuned for instruction following as well as having long-form conversations.
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<br>
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## Evaluation
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We evaluated SynthIA-7B-v1.3 on a wide range of tasks using [Language Model Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) from EleutherAI.
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Here are the results on metrics used by [HuggingFaceH4 Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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import torch, json
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_path = "migtissera/SynthIA-7B-v1.3"
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output_file_path = "./SynthIA-7B-conversations.jsonl"
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model = AutoModelForCausalLM.from_pretrained(
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model_path,
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Please kindly cite using the following BibTeX:
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```
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@misc{SynthIA-7B-v1.3,
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author = {Migel Tissera},
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title = {SynthIA-7B-v1.3: Synthetic Intelligent Agent},
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year = {2023},
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publisher = {GitHub, HuggingFace},
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journal = {GitHub repository, HuggingFace repository},
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