README.md

metadata

language:
  - en
license: cc-by-sa-4.0
tags:
  - causal-lm
  - TensorBlock
  - GGUF
datasets:
  - tiiuae/falcon-refinedweb
  - togethercomputer/RedPajama-Data-1T
  - CarperAI/pilev2-dev
  - bigcode/starcoderdata
  - allenai/peS2o
base_model: stabilityai/stablelm-3b-4e1t
model-index:
  - name: stablelm-3b-4e1t
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: AI2 Reasoning Challenge (25-Shot)
          type: ai2_arc
          config: ARC-Challenge
          split: test
          args:
            num_few_shot: 25
        metrics:
          - type: acc_norm
            value: 46.59
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=stabilityai/stablelm-3b-4e1t
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: HellaSwag (10-Shot)
          type: hellaswag
          split: validation
          args:
            num_few_shot: 10
        metrics:
          - type: acc_norm
            value: 75.94
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=stabilityai/stablelm-3b-4e1t
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU (5-Shot)
          type: cais/mmlu
          config: all
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 45.23
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=stabilityai/stablelm-3b-4e1t
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: TruthfulQA (0-shot)
          type: truthful_qa
          config: multiple_choice
          split: validation
          args:
            num_few_shot: 0
        metrics:
          - type: mc2
            value: 37.2
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=stabilityai/stablelm-3b-4e1t
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: Winogrande (5-shot)
          type: winogrande
          config: winogrande_xl
          split: validation
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 71.19
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=stabilityai/stablelm-3b-4e1t
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GSM8k (5-shot)
          type: gsm8k
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 3.34
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=stabilityai/stablelm-3b-4e1t
          name: Open LLM Leaderboard

stabilityai/stablelm-3b-4e1t - GGUF

This repo contains GGUF format model files for stabilityai/stablelm-3b-4e1t.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

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## Prompt template

Model file specification

Filename	Quant type	File Size	Description
stablelm-3b-4e1t-Q2_K.gguf	Q2_K	1.009 GB	smallest, significant quality loss - not recommended for most purposes
stablelm-3b-4e1t-Q3_K_S.gguf	Q3_K_S	1.168 GB	very small, high quality loss
stablelm-3b-4e1t-Q3_K_M.gguf	Q3_K_M	1.296 GB	very small, high quality loss
stablelm-3b-4e1t-Q3_K_L.gguf	Q3_K_L	1.405 GB	small, substantial quality loss
stablelm-3b-4e1t-Q4_0.gguf	Q4_0	1.498 GB	legacy; small, very high quality loss - prefer using Q3_K_M
stablelm-3b-4e1t-Q4_K_S.gguf	Q4_K_S	1.509 GB	small, greater quality loss
stablelm-3b-4e1t-Q4_K_M.gguf	Q4_K_M	1.591 GB	medium, balanced quality - recommended
stablelm-3b-4e1t-Q5_0.gguf	Q5_0	1.809 GB	legacy; medium, balanced quality - prefer using Q4_K_M
stablelm-3b-4e1t-Q5_K_S.gguf	Q5_K_S	1.809 GB	large, low quality loss - recommended
stablelm-3b-4e1t-Q5_K_M.gguf	Q5_K_M	1.856 GB	large, very low quality loss - recommended
stablelm-3b-4e1t-Q6_K.gguf	Q6_K	2.138 GB	very large, extremely low quality loss
stablelm-3b-4e1t-Q8_0.gguf	Q8_0	2.769 GB	very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/stablelm-3b-4e1t-GGUF --include "stablelm-3b-4e1t-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/stablelm-3b-4e1t-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'