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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+Llama-160M-Chat-v1 - GGUF
+- Model creator: https://huggingface.co/Felladrin/
+- Original model: https://huggingface.co/Felladrin/Llama-160M-Chat-v1/
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [Llama-160M-Chat-v1.Q2_K.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q2_K.gguf) | Q2_K | 0.07GB |
+| [Llama-160M-Chat-v1.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.IQ3_XS.gguf) | IQ3_XS | 0.07GB |
+| [Llama-160M-Chat-v1.IQ3_S.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.IQ3_S.gguf) | IQ3_S | 0.07GB |
+| [Llama-160M-Chat-v1.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q3_K_S.gguf) | Q3_K_S | 0.07GB |
+| [Llama-160M-Chat-v1.IQ3_M.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.IQ3_M.gguf) | IQ3_M | 0.08GB |
+| [Llama-160M-Chat-v1.Q3_K.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q3_K.gguf) | Q3_K | 0.08GB |
+| [Llama-160M-Chat-v1.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q3_K_M.gguf) | Q3_K_M | 0.08GB |
+| [Llama-160M-Chat-v1.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q3_K_L.gguf) | Q3_K_L | 0.08GB |
+| [Llama-160M-Chat-v1.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.IQ4_XS.gguf) | IQ4_XS | 0.09GB |
+| [Llama-160M-Chat-v1.Q4_0.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q4_0.gguf) | Q4_0 | 0.09GB |
+| [Llama-160M-Chat-v1.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.IQ4_NL.gguf) | IQ4_NL | 0.09GB |
+| [Llama-160M-Chat-v1.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q4_K_S.gguf) | Q4_K_S | 0.09GB |
+| [Llama-160M-Chat-v1.Q4_K.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q4_K.gguf) | Q4_K | 0.1GB |
+| [Llama-160M-Chat-v1.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q4_K_M.gguf) | Q4_K_M | 0.1GB |
+| [Llama-160M-Chat-v1.Q4_1.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q4_1.gguf) | Q4_1 | 0.1GB |
+| [Llama-160M-Chat-v1.Q5_0.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q5_0.gguf) | Q5_0 | 0.11GB |
+| [Llama-160M-Chat-v1.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q5_K_S.gguf) | Q5_K_S | 0.11GB |
+| [Llama-160M-Chat-v1.Q5_K.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q5_K.gguf) | Q5_K | 0.11GB |
+| [Llama-160M-Chat-v1.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q5_K_M.gguf) | Q5_K_M | 0.11GB |
+| [Llama-160M-Chat-v1.Q5_1.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q5_1.gguf) | Q5_1 | 0.12GB |
+| [Llama-160M-Chat-v1.Q6_K.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q6_K.gguf) | Q6_K | 0.12GB |
+| [Llama-160M-Chat-v1.Q8_0.gguf](https://huggingface.co/RichardErkhov/Felladrin_-_Llama-160M-Chat-v1-gguf/blob/main/Llama-160M-Chat-v1.Q8_0.gguf) | Q8_0 | 0.16GB |
+
+
+
+
+Original model description:
+---
+language:
+- en
+license: apache-2.0
+tags:
+- text-generation
+base_model: JackFram/llama-160m
+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
+---
+
+# A Llama Chat Model of 160M Parameters
+
+- Base model: [JackFram/llama-160m](https://huggingface.co/JackFram/llama-160m)
+- Datasets:
+  - [ehartford/wizard_vicuna_70k_unfiltered](https://huggingface.co/datasets/ehartford/wizard_vicuna_70k_unfiltered)
+  - [totally-not-an-llm/EverythingLM-data-V3](https://huggingface.co/datasets/totally-not-an-llm/EverythingLM-data-V3)
+  - [Open-Orca/SlimOrca-Dedup](https://huggingface.co/datasets/Open-Orca/SlimOrca-Dedup)
+  - [databricks/databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k)
+  - [THUDM/webglm-qa](https://huggingface.co/datasets/THUDM/webglm-qa)
+- Availability in other ML formats:
+  - GGUF: [Felladrin/gguf-Llama-160M-Chat-v1](https://huggingface.co/Felladrin/gguf-Llama-160M-Chat-v1)
+  - ONNX: [Felladrin/onnx-Llama-160M-Chat-v1](https://huggingface.co/Felladrin/onnx-Llama-160M-Chat-v1)
+  - MLC: [Felladrin/mlc-q4f16-Llama-160M-Chat-v1](https://huggingface.co/Felladrin/mlc-q4f16-Llama-160M-Chat-v1)
+  - MLX: [mlx-community/Llama-160M-Chat-v1-4bit-mlx](https://huggingface.co/mlx-community/Llama-160M-Chat-v1-4bit-mlx)
+
+## Recommended Prompt Format
+
+```
+<|im_start|>system
+{system_message}<|im_end|>
+<|im_start|>user
+{user_message}<|im_end|>
+<|im_start|>assistant
+```
+
+## Recommended Inference Parameters
+
+```yml
+penalty_alpha: 0.5
+top_k: 4
+repetition_penalty: 1.01
+```
+
+## Usage Example
+
+```python
+from transformers import pipeline
+
+generate = pipeline("text-generation", "Felladrin/Llama-160M-Chat-v1")
+
+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?",
+    },
+]
+
+prompt = generate.tokenizer.apply_chat_template(
+    messages, tokenize=False, add_generation_prompt=True
+)
+
+output = generate(
+    prompt,
+    max_new_tokens=1024,
+    penalty_alpha=0.5,
+    top_k=4,
+    repetition_penalty=1.01,
+)
+
+print(output[0]["generated_text"])
+```
+
+## [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Felladrin__Llama-160M-Chat-v1)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |30.27|
+|AI2 Reasoning Challenge (25-Shot)|24.74|
+|HellaSwag (10-Shot)              |35.29|
+|MMLU (5-Shot)                    |26.13|
+|TruthfulQA (0-shot)              |44.16|
+|Winogrande (5-shot)              |51.30|
+|GSM8k (5-shot)                   | 0.00|
+
+