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Model: QuantFactory/Llama3.2-3B-Enigma-GGUF Source: Original Platform
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---
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language:
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- en
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license: llama3.2
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tags:
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- enigma
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- valiant
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- valiant-labs
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- llama
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- llama-3.2
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- llama-3.2-instruct
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- llama-3.2-instruct-3b
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- llama-3
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- llama-3-instruct
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- llama-3-instruct-3b
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- 3b
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- code
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- code-instruct
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- python
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- conversational
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- chat
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- instruct
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base_model: meta-llama/Llama-3.2-3B-Instruct
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datasets:
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- sequelbox/Tachibana
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- sequelbox/Supernova
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pipeline_tag: text-generation
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model_type: llama
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model-index:
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- name: Llama3.2-3B-Enigma
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-Shot)
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type: winogrande
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 67.96
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name: acc
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: ARC Challenge (25-Shot)
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type: arc-challenge
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 47.18
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name: normalized accuracy
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: IFEval (0-Shot)
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type: HuggingFaceH4/ifeval
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args:
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num_few_shot: 0
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metrics:
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- type: inst_level_strict_acc and prompt_level_strict_acc
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value: 47.75
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name: strict accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.2-3B-Enigma
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: BBH (3-Shot)
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type: BBH
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args:
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num_few_shot: 3
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metrics:
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- type: acc_norm
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value: 18.81
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.2-3B-Enigma
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MATH Lvl 5 (4-Shot)
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type: hendrycks/competition_math
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args:
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num_few_shot: 4
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metrics:
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- type: exact_match
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value: 6.65
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name: exact match
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.2-3B-Enigma
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GPQA (0-shot)
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type: Idavidrein/gpqa
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 1.45
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.2-3B-Enigma
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MuSR (0-shot)
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type: TAUR-Lab/MuSR
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 4.54
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.2-3B-Enigma
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU-PRO (5-shot)
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type: TIGER-Lab/MMLU-Pro
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 15.41
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name: accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.2-3B-Enigma
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name: Open LLM Leaderboard
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---
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[](https://hf.co/QuantFactory)
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# QuantFactory/Llama3.2-3B-Enigma-GGUF
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This is quantized version of [ValiantLabs/Llama3.2-3B-Enigma](https://huggingface.co/ValiantLabs/Llama3.2-3B-Enigma) created using llama.cpp
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# Original Model Card
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Enigma is a code-instruct model built on Llama 3.2 3b.
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- High quality code instruct performance with the Llama 3.2 Instruct chat format
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- Finetuned on synthetic code-instruct data generated with Llama 3.1 405b. [Find the current version of the dataset here!](https://huggingface.co/datasets/sequelbox/Tachibana)
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- Overall chat performance supplemented with [generalist synthetic data.](https://huggingface.co/datasets/sequelbox/Supernova)
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## Version
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This is the **2024-09-30** release of Enigma for Llama 3.2 3b, enhancing code-instruct and general chat capabilities.
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Enigma is also available for [Llama 3.1 8b!](https://huggingface.co/ValiantLabs/Llama3.1-8B-Enigma)
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Help us and recommend Enigma to your friends! We're excited for more Enigma releases in the future.
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## Prompting Guide
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Enigma uses the [Llama 3.2 Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) prompt format. The example script below can be used as a starting point for general chat:
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```python
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import transformers
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import torch
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model_id = "ValiantLabs/Llama3.2-3B-Enigma"
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pipeline = transformers.pipeline(
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"text-generation",
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model=model_id,
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model_kwargs={"torch_dtype": torch.bfloat16},
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device_map="auto",
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)
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messages = [
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{"role": "system", "content": "You are Enigma, a highly capable code assistant."},
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{"role": "user", "content": "Can you explain virtualization to me?"}
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]
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outputs = pipeline(
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messages,
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max_new_tokens=1024,
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)
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print(outputs[0]["generated_text"][-1])
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```
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## The Model
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Enigma is built on top of Llama 3.2 3b Instruct, using high quality code-instruct data and general chat data in Llama 3.2 Instruct prompt style to supplement overall performance.
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Our current version of Enigma is trained on code-instruct data from [sequelbox/Tachibana](https://huggingface.co/datasets/sequelbox/Tachibana) and general chat data from [sequelbox/Supernova.](https://huggingface.co/datasets/sequelbox/Supernova)
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Enigma is created by [Valiant Labs.](http://valiantlabs.ca/)
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[Check out our HuggingFace page for Shining Valiant 2 and our other Build Tools models for creators!](https://huggingface.co/ValiantLabs)
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[Follow us on X for updates on our models!](https://twitter.com/valiant_labs)
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We care about open source.
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For everyone to use.
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We encourage others to finetune further from our models.
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1
configuration.json
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configuration.json
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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