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README.md

@@ -0,0 +1,347 @@
+---
+language:
+- en
+license: apache-2.0
+tags:
+- text-generation
+- TensorBlock
+- GGUF
+base_model: Felladrin/Llama-160M-Chat-v1
+datasets:
+- ehartford/wizard_vicuna_70k_unfiltered
+- totally-not-an-llm/EverythingLM-data-V3
+- Open-Orca/SlimOrca-Dedup
+- databricks/databricks-dolly-15k
+- THUDM/webglm-qa
+widget:
+- messages:
+  - role: system
+    content: You are a helpful assistant, who answers with empathy.
+  - role: user
+    content: Got a question for you!
+  - role: assistant
+    content: Sure! What's it?
+  - role: user
+    content: Why do you love cats so much!? 🐈
+- messages:
+  - role: system
+    content: You are a helpful assistant who answers user's questions with empathy.
+  - role: user
+    content: Who is Mona Lisa?
+- messages:
+  - role: system
+    content: You are a helpful assistant who provides concise responses.
+  - role: user
+    content: Heya!
+  - role: assistant
+    content: Hi! How may I help you today?
+  - role: user
+    content: I need to build a simple website. Where should I start learning about
+      web development?
+- messages:
+  - role: user
+    content: Invited some friends to come home today. Give me some ideas for games
+      to play with them!
+- messages:
+  - role: system
+    content: You are a helpful assistant who answers user's questions with details
+      and curiosity.
+  - role: user
+    content: What are some potential applications for quantum computing?
+- messages:
+  - role: system
+    content: You are a helpful assistant who gives creative responses.
+  - role: user
+    content: Write the specs of a game about mages in a fantasy world.
+- messages:
+  - role: system
+    content: You are a helpful assistant who answers user's questions with details.
+  - role: user
+    content: Tell me about the pros and cons of social media.
+- messages:
+  - role: system
+    content: You are a helpful assistant who answers user's questions with confidence.
+  - role: user
+    content: What is a dog?
+  - role: assistant
+    content: A dog is a four-legged, domesticated animal that is a member of the class
+      Mammalia, which includes all mammals. Dogs are known for their loyalty, playfulness,
+      and ability to be trained for various tasks. They are also used for hunting,
+      herding, and as service animals.
+  - role: user
+    content: What is the color of an apple?
+inference:
+  parameters:
+    max_new_tokens: 250
+    penalty_alpha: 0.5
+    top_k: 4
+    repetition_penalty: 1.01
+model-index:
+- name: Llama-160M-Chat-v1
+  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: 24.74
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-160M-Chat-v1
+      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: 35.29
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-160M-Chat-v1
+      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: 26.13
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-160M-Chat-v1
+      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: 44.16
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-160M-Chat-v1
+      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: 51.3
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-160M-Chat-v1
+      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: 0.0
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-160M-Chat-v1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: IFEval (0-Shot)
+      type: HuggingFaceH4/ifeval
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: inst_level_strict_acc and prompt_level_strict_acc
+      value: 15.75
+      name: strict accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Felladrin/Llama-160M-Chat-v1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BBH (3-Shot)
+      type: BBH
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc_norm
+      value: 3.17
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Felladrin/Llama-160M-Chat-v1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MATH Lvl 5 (4-Shot)
+      type: hendrycks/competition_math
+      args:
+        num_few_shot: 4
+    metrics:
+    - type: exact_match
+      value: 0.0
+      name: exact match
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Felladrin/Llama-160M-Chat-v1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GPQA (0-shot)
+      type: Idavidrein/gpqa
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 1.01
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Felladrin/Llama-160M-Chat-v1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MuSR (0-shot)
+      type: TAUR-Lab/MuSR
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 3.17
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Felladrin/Llama-160M-Chat-v1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU-PRO (5-shot)
+      type: TIGER-Lab/MMLU-Pro
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 1.51
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Felladrin/Llama-160M-Chat-v1
+      name: Open LLM Leaderboard
+---
+
+<div style="width: auto; margin-left: auto; margin-right: auto">
+<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
+</div>
+<div style="display: flex; justify-content: space-between; width: 100%;">
+    <div style="display: flex; flex-direction: column; align-items: flex-start;">
+        <p style="margin-top: 0.5em; margin-bottom: 0em;">
+            Feedback and support: TensorBlock's  <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
+        </p>
+    </div>
+</div>
+
+## Felladrin/Llama-160M-Chat-v1 - GGUF
+
+This repo contains GGUF format model files for [Felladrin/Llama-160M-Chat-v1](https://huggingface.co/Felladrin/Llama-160M-Chat-v1).
+
+The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
+
+<div style="text-align: left; margin: 20px 0;">
+    <a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
+        Run them on the TensorBlock client using your local machine ↗
+    </a>
+</div>
+
+## Prompt template
+
+```
+<|im_start|>system
+{system_prompt}<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant
+```
+
+## Model file specification
+
+| Filename | Quant type | File Size | Description |
+| -------- | ---------- | --------- | ----------- |
+| [Llama-160M-Chat-v1-Q2_K.gguf](https://huggingface.co/tensorblock/Llama-160M-Chat-v1-GGUF/blob/main/Llama-160M-Chat-v1-Q2_K.gguf) | Q2_K | 0.066 GB | smallest, significant quality loss - not recommended for most purposes |
+| [Llama-160M-Chat-v1-Q3_K_S.gguf](https://huggingface.co/tensorblock/Llama-160M-Chat-v1-GGUF/blob/main/Llama-160M-Chat-v1-Q3_K_S.gguf) | Q3_K_S | 0.075 GB | very small, high quality loss |
+| [Llama-160M-Chat-v1-Q3_K_M.gguf](https://huggingface.co/tensorblock/Llama-160M-Chat-v1-GGUF/blob/main/Llama-160M-Chat-v1-Q3_K_M.gguf) | Q3_K_M | 0.080 GB | very small, high quality loss |
+| [Llama-160M-Chat-v1-Q3_K_L.gguf](https://huggingface.co/tensorblock/Llama-160M-Chat-v1-GGUF/blob/main/Llama-160M-Chat-v1-Q3_K_L.gguf) | Q3_K_L | 0.085 GB | small, substantial quality loss |
+| [Llama-160M-Chat-v1-Q4_0.gguf](https://huggingface.co/tensorblock/Llama-160M-Chat-v1-GGUF/blob/main/Llama-160M-Chat-v1-Q4_0.gguf) | Q4_0 | 0.092 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| [Llama-160M-Chat-v1-Q4_K_S.gguf](https://huggingface.co/tensorblock/Llama-160M-Chat-v1-GGUF/blob/main/Llama-160M-Chat-v1-Q4_K_S.gguf) | Q4_K_S | 0.092 GB | small, greater quality loss |
+| [Llama-160M-Chat-v1-Q4_K_M.gguf](https://huggingface.co/tensorblock/Llama-160M-Chat-v1-GGUF/blob/main/Llama-160M-Chat-v1-Q4_K_M.gguf) | Q4_K_M | 0.096 GB | medium, balanced quality - recommended |
+| [Llama-160M-Chat-v1-Q5_0.gguf](https://huggingface.co/tensorblock/Llama-160M-Chat-v1-GGUF/blob/main/Llama-160M-Chat-v1-Q5_0.gguf) | Q5_0 | 0.108 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| [Llama-160M-Chat-v1-Q5_K_S.gguf](https://huggingface.co/tensorblock/Llama-160M-Chat-v1-GGUF/blob/main/Llama-160M-Chat-v1-Q5_K_S.gguf) | Q5_K_S | 0.108 GB | large, low quality loss - recommended |
+| [Llama-160M-Chat-v1-Q5_K_M.gguf](https://huggingface.co/tensorblock/Llama-160M-Chat-v1-GGUF/blob/main/Llama-160M-Chat-v1-Q5_K_M.gguf) | Q5_K_M | 0.110 GB | large, very low quality loss - recommended |
+| [Llama-160M-Chat-v1-Q6_K.gguf](https://huggingface.co/tensorblock/Llama-160M-Chat-v1-GGUF/blob/main/Llama-160M-Chat-v1-Q6_K.gguf) | Q6_K | 0.125 GB | very large, extremely low quality loss |
+| [Llama-160M-Chat-v1-Q8_0.gguf](https://huggingface.co/tensorblock/Llama-160M-Chat-v1-GGUF/blob/main/Llama-160M-Chat-v1-Q8_0.gguf) | Q8_0 | 0.161 GB | very large, extremely low quality loss - not recommended |
+
+
+## Downloading instruction
+
+### Command line
+
+Firstly, install Huggingface Client
+
+```shell
+pip install -U "huggingface_hub[cli]"
+```
+
+Then, downoad the individual model file the a local directory
+
+```shell
+huggingface-cli download tensorblock/Llama-160M-Chat-v1-GGUF --include "Llama-160M-Chat-v1-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:
+
+```shell
+huggingface-cli download tensorblock/Llama-160M-Chat-v1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
+```