---
base_model: Writer/Palmyra-Med-70B-32K
language:
- en
license: other
license_name: writer-open-model-license
license_link: https://writer.com/legal/open-model-license/
tags:
- instruct
- finetune
- DPO
- distillation
- heathcare
- medical
- clinical
- med
- lifescience
- Pharmaceutical
- Pharma
- Enterprise LLM
- Enterprise
- Enterprise ready
- mlc-ai
- MLC-Weight-Conversion
extra_gated_prompt: By clicking "Agree", you agree to the [License Agreement](https://writer.com/legal/open-model-license/)
  and acknowledge Writer's [Privacy Policy](https://writer.com/legal/acceptable-use/).
extra_gated_fields:
  Name: text
  Email: text
  Organization or Affiliation: text
  Receive email updates and promotions on Writer products, services, and research?:
    type: select
    options:
    - 'Yes'
    - 'No'
  I acknowledge that this model is for non-commercial use only unless I acquire a separate license from Writer: checkbox
widget:
- example_title: Palmyra-Med-70B-32k
  messages:
  - role: system
    content: You are a highly knowledgeable and experienced expert in the healthcare
      and biomedical field, possessing extensive medical knowledge and practical expertise.
  - role: user
    content: Does danzhi Xiaoyao San ameliorate depressive-like behavior by shifting
      toward serotonin via the downregulation of hippocampal indoleamine 2,3-dioxygenase?
  output:
    text: Danzhi Xiaoyao San (DXS) exhibited significant antidepressant-like effects
      in rats subjected to chronic unpredictable mild stress (CUMS), a commonly used
      model for inducing depressive-like behavior. The administration of DXS led to
      a notable reduction in the activity of indoleamine 2,3-dioxygenase (IDO) in
      the hippocampus. This reduction in IDO activity is crucial because IDO is an
      enzyme that catalyzes the degradation of tryptophan into kynurenine (Kyn), thereby
      diverting tryptophan away from the serotonin (5-HT) synthesis pathway. By downregulating
      IDO, DXS effectively shifts the balance of tryptophan metabolism towards increased
      serotonin production, thereby enhancing the availability of serotonin. This
      shift in the Kyn/5-HT pathway favoring serotonin is likely a key mechanism underlying
      the antidepressant effects observed with DXS treatment. Enhanced serotonin levels
      in the hippocampus are associated with improved mood and reduction of depressive
      symptoms, suggesting that DXS could be a promising therapeutic agent for managing
      depression.
model-index:
- name: Palmyra-Med-70B-32k
  results: []
---
---
library_name: mlc-llm
base_model: Writer/Palmyra-Med-70B-32K
tags:
- mlc-llm
- web-llm
---

# codegood/Palmyra-Med-70B-32K-q4f16_1-MLC

This is the [Palmyra-Med-70B-32K](https://huggingface.co/Writer/Palmyra-Med-70B-32K) model in MLC format `q4f16_1`.
The conversion was done using the [MLC-Weight-Conversion](https://huggingface.co/spaces/mlc-ai/MLC-Weight-Conversion) space.
The model can be used for projects [MLC-LLM](https://github.com/mlc-ai/mlc-llm) and [WebLLM](https://github.com/mlc-ai/web-llm).

## Example Usage

Here are some examples of using this model in MLC LLM.
Before running the examples, please install MLC LLM by following the [installation documentation](https://llm.mlc.ai/docs/install/mlc_llm.html#install-mlc-packages).

### Chat

In command line, run
```bash
mlc_llm chat HF://mlc-ai/codegood/Palmyra-Med-70B-32K-q4f16_1-MLC
```

### REST Server

In command line, run
```bash
mlc_llm serve HF://mlc-ai/codegood/Palmyra-Med-70B-32K-q4f16_1-MLC
```

### Python API

```python
from mlc_llm import MLCEngine

# Create engine
model = "HF://mlc-ai/codegood/Palmyra-Med-70B-32K-q4f16_1-MLC"
engine = MLCEngine(model)

# Run chat completion in OpenAI API.
for response in engine.chat.completions.create(
    messages=[{"role": "user", "content": "What is the meaning of life?"}],
    model=model,
    stream=True,
):
    for choice in response.choices:
        print(choice.delta.content, end="", flush=True)
print("\n")

engine.terminate()
```

## Documentation

For more information on MLC LLM project, please visit our [documentation](https://llm.mlc.ai/docs/) and [GitHub repo](http://github.com/mlc-ai/mlc-llm).