87 lines
2.9 KiB
Markdown
87 lines
2.9 KiB
Markdown
---
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base_model: pints-ai/1.5-Pints-16K-v0.1
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datasets:
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- pints-ai/Expository-Prose-V1
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- HuggingFaceH4/ultrachat_200k
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- Open-Orca/SlimOrca-Dedup
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- meta-math/MetaMathQA
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- HuggingFaceH4/deita-10k-v0-sft
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- WizardLM/WizardLM_evol_instruct_V2_196k
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- togethercomputer/llama-instruct
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- LDJnr/Capybara
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- HuggingFaceH4/ultrafeedback_binarized
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language:
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- en
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license: mit
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pipeline_tag: text-generation
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tags:
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- mlx
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extra_gated_prompt: Though best efforts has been made to ensure, as much as possible,
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that all texts in the training corpora are royalty free, this does not constitute
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a legal guarantee that such is the case. **By using any of the models, corpora or
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part thereof, the user agrees to bear full responsibility to do the necessary due
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diligence to ensure that he / she is in compliance with their local copyright laws.
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Additionally, the user agrees to bear any damages arising as a direct cause (or
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otherwise) of using any artifacts released by the pints research team, as well as
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full responsibility for the consequences of his / her usage (or implementation)
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of any such released artifacts. The user also indemnifies Pints Research Team (and
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any of its members or agents) of any damage, related or unrelated, to the release
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or subsequent usage of any findings, artifacts or code by the team. For the avoidance
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of doubt, any artifacts released by the Pints Research team are done so in accordance
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with the 'fair use' clause of Copyright Law, in hopes that this will aid the research
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community in bringing LLMs to the next frontier.
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extra_gated_fields:
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Company: text
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Country: country
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Specific date: date_picker
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I want to use this model for:
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type: select
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options:
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- Research
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- Education
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- label: Other
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value: other
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I agree to use this model for in accordance to the afore-mentioned Terms of Use: checkbox
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model-index:
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- name: 1.5-Pints
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results:
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- task:
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type: text-generation
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dataset:
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name: MTBench
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type: ai2_arc
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metrics:
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- type: LLM-as-a-Judge
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value: 3.4
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name: MTBench
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source:
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url: https://huggingface.co/spaces/lmsys/mt-bench
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name: MTBench
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---
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# mlx-community/1.5-Pints-16K-v0.1
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The Model [mlx-community/1.5-Pints-16K-v0.1](https://huggingface.co/mlx-community/1.5-Pints-16K-v0.1) was converted to MLX format from [pints-ai/1.5-Pints-16K-v0.1](https://huggingface.co/pints-ai/1.5-Pints-16K-v0.1) using mlx-lm version **0.19.2**.
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## Use with mlx
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```bash
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pip install mlx-lm
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```
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```python
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from mlx_lm import load, generate
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model, tokenizer = load("mlx-community/1.5-Pints-16K-v0.1")
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prompt="hello"
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if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
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messages = [{"role": "user", "content": prompt}]
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prompt = tokenizer.apply_chat_template(
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messages, tokenize=False, add_generation_prompt=True
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)
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response = generate(model, tokenizer, prompt=prompt, verbose=True)
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```
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