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Model: mlx-community/1.5-Pints-16K-v0.1
Source: Original Platform

README.md

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