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.gitattributes

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README.md

@@ -0,0 +1,233 @@
+---
+language:
+- en
+license: apache-2.0
+tags:
+- text-generation
+- TensorBlock
+- GGUF
+datasets:
+- THUDM/webglm-qa
+- databricks/databricks-dolly-15k
+- cognitivecomputations/wizard_vicuna_70k_unfiltered
+- totally-not-an-llm/EverythingLM-data-V3
+- Amod/mental_health_counseling_conversations
+- sablo/oasst2_curated
+- starfishmedical/webGPT_x_dolly
+- Open-Orca/OpenOrca
+- mlabonne/chatml_dpo_pairs
+base_model: Felladrin/Llama-68M-Chat-v1
+widget:
+- messages:
+  - role: system
+    content: You are a career counselor. The user will provide you with an individual
+      looking for guidance in their professional life, and your task is to assist
+      them in determining what careers they are most suited for based on their skills,
+      interests, and experience. You should also conduct research into the various
+      options available, explain the job market trends in different industries, and
+      advice on which qualifications would be beneficial for pursuing particular fields.
+  - role: user
+    content: Heya!
+  - role: assistant
+    content: Hi! How may I help you?
+  - role: user
+    content: I am interested in developing a career in software engineering. What
+      would you recommend me to do?
+- messages:
+  - role: system
+    content: You are a knowledgeable assistant. Help the user as much as you can.
+  - role: user
+    content: How to become healthier?
+- messages:
+  - role: system
+    content: You are a helpful assistant who provides concise responses.
+  - role: user
+    content: Hi!
+  - role: assistant
+    content: Hello there! How may I help you?
+  - role: user
+    content: I need to build a simple website. Where should I start learning about
+      web development?
+- messages:
+  - role: system
+    content: You are a very creative assistant. User will give you a task, which you
+      should complete with all your knowledge.
+  - role: user
+    content: Write the background story of an RPG game about wizards and dragons in
+      a sci-fi world.
+inference:
+  parameters:
+    max_new_tokens: 64
+    penalty_alpha: 0.5
+    top_k: 4
+model-index:
+- name: Llama-68M-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: 23.29
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-68M-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: 28.27
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-68M-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: 25.18
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-68M-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: 47.27
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-68M-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: 54.3
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-68M-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-68M-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-68M-Chat-v1 - GGUF
+
+This repo contains GGUF format model files for [Felladrin/Llama-68M-Chat-v1](https://huggingface.co/Felladrin/Llama-68M-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).
+
+## 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-68M-Chat-v1-Q2_K.gguf](https://huggingface.co/tensorblock/Llama-68M-Chat-v1-GGUF/tree/main/Llama-68M-Chat-v1-Q2_K.gguf) | Q2_K | 0.033 GB | smallest, significant quality loss - not recommended for most purposes |
+| [Llama-68M-Chat-v1-Q3_K_S.gguf](https://huggingface.co/tensorblock/Llama-68M-Chat-v1-GGUF/tree/main/Llama-68M-Chat-v1-Q3_K_S.gguf) | Q3_K_S | 0.037 GB | very small, high quality loss |
+| [Llama-68M-Chat-v1-Q3_K_M.gguf](https://huggingface.co/tensorblock/Llama-68M-Chat-v1-GGUF/tree/main/Llama-68M-Chat-v1-Q3_K_M.gguf) | Q3_K_M | 0.038 GB | very small, high quality loss |
+| [Llama-68M-Chat-v1-Q3_K_L.gguf](https://huggingface.co/tensorblock/Llama-68M-Chat-v1-GGUF/tree/main/Llama-68M-Chat-v1-Q3_K_L.gguf) | Q3_K_L | 0.039 GB | small, substantial quality loss |
+| [Llama-68M-Chat-v1-Q4_0.gguf](https://huggingface.co/tensorblock/Llama-68M-Chat-v1-GGUF/tree/main/Llama-68M-Chat-v1-Q4_0.gguf) | Q4_0 | 0.042 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| [Llama-68M-Chat-v1-Q4_K_S.gguf](https://huggingface.co/tensorblock/Llama-68M-Chat-v1-GGUF/tree/main/Llama-68M-Chat-v1-Q4_K_S.gguf) | Q4_K_S | 0.042 GB | small, greater quality loss |
+| [Llama-68M-Chat-v1-Q4_K_M.gguf](https://huggingface.co/tensorblock/Llama-68M-Chat-v1-GGUF/tree/main/Llama-68M-Chat-v1-Q4_K_M.gguf) | Q4_K_M | 0.043 GB | medium, balanced quality - recommended |
+| [Llama-68M-Chat-v1-Q5_0.gguf](https://huggingface.co/tensorblock/Llama-68M-Chat-v1-GGUF/tree/main/Llama-68M-Chat-v1-Q5_0.gguf) | Q5_0 | 0.047 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| [Llama-68M-Chat-v1-Q5_K_S.gguf](https://huggingface.co/tensorblock/Llama-68M-Chat-v1-GGUF/tree/main/Llama-68M-Chat-v1-Q5_K_S.gguf) | Q5_K_S | 0.047 GB | large, low quality loss - recommended |
+| [Llama-68M-Chat-v1-Q5_K_M.gguf](https://huggingface.co/tensorblock/Llama-68M-Chat-v1-GGUF/tree/main/Llama-68M-Chat-v1-Q5_K_M.gguf) | Q5_K_M | 0.048 GB | large, very low quality loss - recommended |
+| [Llama-68M-Chat-v1-Q6_K.gguf](https://huggingface.co/tensorblock/Llama-68M-Chat-v1-GGUF/tree/main/Llama-68M-Chat-v1-Q6_K.gguf) | Q6_K | 0.053 GB | very large, extremely low quality loss |
+| [Llama-68M-Chat-v1-Q8_0.gguf](https://huggingface.co/tensorblock/Llama-68M-Chat-v1-GGUF/tree/main/Llama-68M-Chat-v1-Q8_0.gguf) | Q8_0 | 0.068 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-68M-Chat-v1-GGUF --include "Llama-68M-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-68M-Chat-v1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
+```