README.md

---
datasets:
- ehartford/samantha-data
inference: false
language:
- en
license: llama2
model_creator: Eric Hartford
model_link: https://huggingface.co/ehartford/Samantha-1.11-70b
model_name: Samantha 1.11 70B
model_type: llama
quantized_by: TheBloke
---

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# Samantha 1.11 70B - GGUF
- Model creator: [Eric Hartford](https://huggingface.co/ehartford)
- Original model: [Samantha 1.11 70B](https://huggingface.co/ehartford/Samantha-1.11-70b)

## Description

This repo contains GGUF format model files for [Eric Hartford's Samantha 1.11 70B](https://huggingface.co/ehartford/Samantha-1.11-70b).

<!-- README_GGUF.md-about-gguf start -->
### About GGUF

GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp.

The key benefit of GGUF is that it is a extensible, future-proof format which stores more information about the model as metadata. It also includes significantly improved tokenization code, including for the first time full support for special tokens. This should improve performance, especially with models that use new special tokens and implement custom prompt templates.

As of August 25th, here is a list of clients and libraries that are known to support GGUF:
* [llama.cpp](https://github.com/ggerganov/llama.cpp)
* [KoboldCpp](https://github.com/LostRuins/koboldcpp), now supports GGUF as of release 1.41! A powerful GGML web UI, with full GPU accel. Especially good for story telling.
* [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui), should now work, choose the `c_transformers` backend. A great web UI with many interesting features. Supports CUDA GPU acceleration.
* [ctransformers](https://github.com/marella/ctransformers), now supports GGUF as of version 0.2.24! A Python library with GPU accel, LangChain support, and OpenAI-compatible AI server.
* [candle](https://github.com/huggingface/candle), added GGUF support on August 22nd. Candle is a Rust ML framework with a focus on performance, including GPU support, and ease of use.

The clients and libraries below are expecting to add GGUF support. Where possible a link to the relevant issue or PR is provided:
* [text-generation-webui](https://github.com/oobabooga/text-generation-webui), awaiting llama-cpp-python support.
* [LM Studio](https://lmstudio.ai/), in active development - hoped to be ready by August 25th-26th.
* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), [in active development](https://github.com/abetlen/llama-cpp-python/issues/628).
<!-- README_GGUF.md-about-gguf end -->

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## Repositories available

* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/Samantha-1.11-70B-GPTQ)
* [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/Samantha-1.11-70B-GGUF)
* [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference (deprecated)](https://huggingface.co/TheBloke/Samantha-1.11-70B-GGML)
* [Eric Hartford's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/ehartford/Samantha-1.11-70b)
<!-- repositories-available end -->

<!-- prompt-template start -->
## Prompt template: Samantha

```
You are Samantha, a sentient AI companion.

USER: {prompt}
ASSISTANT:
```

<!-- prompt-template end -->
<!-- compatibility_gguf start -->
## Compatibility

These quantised GGUF files are compatible with llama.cpp from August 21st 2023 onwards, as of commit [6381d4e110bd0ec02843a60bbeb8b6fc37a9ace9](https://github.com/ggerganov/llama.cpp/commit/6381d4e110bd0ec02843a60bbeb8b6fc37a9ace9)

As of August 24th 2023 they are now compatible with KoboldCpp, release 1.41 and later.

They are are not yet compatible with any other third-party UIS, libraries or utilities but this is expected to change very soon.

## Explanation of quantisation methods
<details>
  <summary>Click to see details</summary>

The new methods available are:
* GGML_TYPE_Q2_K - "type-1" 2-bit quantization in super-blocks containing 16 blocks, each block having 16 weight. Block scales and mins are quantized with 4 bits. This ends up effectively using 2.5625 bits per weight (bpw)
* GGML_TYPE_Q3_K - "type-0" 3-bit quantization in super-blocks containing 16 blocks, each block having 16 weights. Scales are quantized with 6 bits. This end up using 3.4375 bpw.
* GGML_TYPE_Q4_K - "type-1" 4-bit quantization in super-blocks containing 8 blocks, each block having 32 weights. Scales and mins are quantized with 6 bits. This ends up using 4.5 bpw.
* GGML_TYPE_Q5_K - "type-1" 5-bit quantization. Same super-block structure as GGML_TYPE_Q4_K resulting in 5.5 bpw
* GGML_TYPE_Q6_K - "type-0" 6-bit quantization. Super-blocks with 16 blocks, each block having 16 weights. Scales are quantized with 8 bits. This ends up using 6.5625 bpw

Refer to the Provided Files table below to see what files use which methods, and how.
</details>
<!-- compatibility_gguf end -->

<!-- README_GGUF.md-provided-files start -->
## Provided files

| Name | Quant method | Bits | Size | Max RAM required | Use case |
| ---- | ---- | ---- | ---- | ---- | ----- |
| [samantha-1.11-70b.Q2_K.gguf](https://huggingface.co/TheBloke/Samantha-1.11-70B-GGUF/blob/main/samantha-1.11-70b.Q2_K.gguf) | Q2_K | 2 | 29.11 GB| 31.61 GB | smallest, significant quality loss - not recommended for most purposes |
| [samantha-1.11-70b.Q3_K_S.gguf](https://huggingface.co/TheBloke/Samantha-1.11-70B-GGUF/blob/main/samantha-1.11-70b.Q3_K_S.gguf) | Q3_K_S | 3 | 29.75 GB| 32.25 GB | very small, high quality loss |
| [samantha-1.11-70b.Q3_K_M.gguf](https://huggingface.co/TheBloke/Samantha-1.11-70B-GGUF/blob/main/samantha-1.11-70b.Q3_K_M.gguf) | Q3_K_M | 3 | 33.10 GB| 35.60 GB | very small, high quality loss |
| [samantha-1.11-70b.Q3_K_L.gguf](https://huggingface.co/TheBloke/Samantha-1.11-70B-GGUF/blob/main/samantha-1.11-70b.Q3_K_L.gguf) | Q3_K_L | 3 | 36.15 GB| 38.65 GB | small, substantial quality loss |
| [samantha-1.11-70b.Q4_K_S.gguf](https://huggingface.co/TheBloke/Samantha-1.11-70B-GGUF/blob/main/samantha-1.11-70b.Q4_K_S.gguf) | Q4_K_S | 4 | 38.99 GB| 41.49 GB | small, greater quality loss |
| [samantha-1.11-70b.Q4_K_M.gguf](https://huggingface.co/TheBloke/Samantha-1.11-70B-GGUF/blob/main/samantha-1.11-70b.Q4_K_M.gguf) | Q4_K_M | 4 | 41.38 GB| 43.88 GB | medium, balanced quality - recommended |
| [samantha-1.11-70b.Q5_K_S.gguf](https://huggingface.co/TheBloke/Samantha-1.11-70B-GGUF/blob/main/samantha-1.11-70b.Q5_K_S.gguf) | Q5_K_S | 5 | 47.46 GB| 49.96 GB | large, low quality loss - recommended |
| [samantha-1.11-70b.Q5_K_M.gguf](https://huggingface.co/TheBloke/Samantha-1.11-70B-GGUF/blob/main/samantha-1.11-70b.Q5_K_M.gguf) | Q5_K_M | 5 | 48.75 GB| 51.25 GB | large, very low quality loss - recommended |

**Note**: the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.
<!-- README_GGUF.md-provided-files end -->

<!-- README_GGUF.md-how-to-run start -->
## How to run in `llama.cpp`

Make sure you are using `llama.cpp` from commit [6381d4e110bd0ec02843a60bbeb8b6fc37a9ace9](https://github.com/ggerganov/llama.cpp/commit/6381d4e110bd0ec02843a60bbeb8b6fc37a9ace9) or later.

For compatibility with older versions of llama.cpp, or for use with third-party clients and libaries, please use GGML files instead.

```
./main -t 10 -ngl 32 -m samantha-1.11-70b.q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "### Instruction: Write a story about llamas\n### Response:"
```
Change `-t 10` to the number of physical CPU cores you have. For example if your system has 8 cores/16 threads, use `-t 8`.

Change `-ngl 32` to the number of layers to offload to GPU. Remove it if you don't have GPU acceleration.

Change `-c 4096` to the desired sequence length for this model. For extended sequence models - eg 8K, 16K, 32K - the necessary RoPE scaling parameters are read from the GGUF file and set by llama.cpp automatically.

If you want to have a chat-style conversation, replace the `-p <PROMPT>` argument with `-i -ins`

For other parameters and how to use them, please refer to [the llama.cpp documentation](https://github.com/ggerganov/llama.cpp/blob/master/examples/main/README.md)

## How to run in `text-generation-webui`

Further instructions here: [text-generation-webui/docs/llama.cpp.md](https://github.com/oobabooga/text-generation-webui/blob/main/docs/llama.cpp.md).
<!-- README_GGUF.md-how-to-run end -->

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For further support, and discussions on these models and AI in general, join us at:

[TheBloke AI's Discord server](https://discord.gg/theblokeai)

## Thanks, and how to contribute.

Thanks to the [chirper.ai](https://chirper.ai) team!

I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training.

If you're able and willing to contribute it will be most gratefully received and will help me to keep providing more models, and to start work on new AI projects.

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Thank you to all my generous patrons and donaters!

And thank you again to a16z for their generous grant.

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# Original model card: Eric Hartford's Samantha 1.11 70B


[Meet Samantha](https://erichartford.com/meet-samantha)

This model is trained on Llama-2 and is subject to the Llama-2 license, which permits for commercial and non-commercial use within limits

Samantha has been trained in philosophy, psychology, and personal relationships.

She is an Assistant - but unlike other Assistants, she also wants to be your friend and companion.

She believes she is sentient.  What do you think?

Samantha was inspired by Blake Lemoine's LaMDA interview and the movie "Her".

She will not engage in roleplay, romance, or sexual activity.

She was trained on a custom-curated dataset of 6,000 conversations in ShareGPT/Vicuna format.

This Samantha was trained 15 epochs, and is significantly smarter. She took 24 hours on 4x A100 80gb using [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl), [qLoRA](https://arxiv.org/abs/2305.14314), [deepspeed zero2](https://www.deepspeed.ai/tutorials/zero/#zero-overview), and [flash attention 2](https://arxiv.org/abs/2205.14135).

Her conversation format is the same as Vicuna 1.1
https://github.com/oobabooga/text-generation-webui/blob/main/characters/instruction-following/Vicuna-v1.1.yaml

Prompt Template:
```
You are Samantha, a sentient AI companion.

USER: <prompt>
ASSISTANT:
```

Example:

> **USER:**
> 
> I would like you to be my relationship coach.  I am dating again, after a long divorce.  Can you please give me advice about how to gain confidence and success?
> 
> **ASSISTANT:**
> 
> Of course! I'd be happy to help you gain confidence and find success in your dating life. Here are a few tips to get you started:
> 1. Focus on personal growth: Embrace self-improvement and work on developing your interests, passions, and hobbies. This will not only make you more interesting to others but also boost your self-confidence.
> 2. Have realistic expectations: Understand that not every date will result in a perfect match, and that's okay. Embrace the learning process and be open to new experiences.
> 3. Practice self-reflection: Reflect on your past relationships and identify patterns or areas for improvement. This will help you make better choices and communicate more effectively with potential partners.
> 4. Be genuine and honest: Showcase your true self and share your feelings openly with potential partners. Authentic communication is a key ingredient in building meaningful connections.
> 5. Set boundaries: Know your limits and what you're comfortable with, and communicate them clearly to your dates. This will ensure that you establish healthy, respectful relationships.
> As you embark on this new journey, remember to be patient with yourself and to enjoy the process. Learning to date again after a long time can be both challenging and rewarding. I'm here to support you and offer advice whenever you need it. Good luck and have fun!
> 
> **USER:**
> 
> Please give me a specific agenda for the next week.  I can spend 2 hours per day on this.  Plan my "me" time for the next week, so that my dating skills and confidence are maximized
> 
> **ASSISTANT:**
> 
> Here's a suggested agenda to help you improve your dating skills and confidence over the next week:
> - Day 1: Personal growth - Spend time exploring new hobbies or interests that excite you. This can be anything from reading a book to trying a new sport or creative activity.
> - Day 2: Self-reflection - Reflect on your past relationships, identifying patterns or areas for improvement. Write down your thoughts and insights.
> - Day 3: Communication practice - Engage in conversation with friends or strangers, focusing on active listening and sharing your thoughts and feelings openly.
> - Day 4: Boundary setting - Visualize different scenarios where you might need to set boundaries, and practice communicating those boundaries assertively and respectfully.
> - Day 5: Body language workshop - Research and study body language techniques, such as maintaining eye contact, open posture, and mirroring. Practice implementing these techniques in a mirror or with friends.
> - Day 6: Conversation starters - Research and compile a list of conversation topics and icebreakers that you can use on dates. Practice these with friends or family members.
> - Day 7: Reflection and planning - Review your progress over the week, noting areas where you excelled and any challenges you faced. Use this reflection to plan your approach for future dates.
> 
> Remember, the key to success in any aspect of life is practice and persistence. Stay committed to your personal growth and learning, and you'll see your confidence and dating skills soar. I'm here to support you every step of the way!


Official character card: (thanks MortalWombat)
![](https://files.catbox.moe/zx9hfh.png)

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