| Name | echolib JSON |
| Version |
0.2.0
JSON |
| download |
| home_page | https://github.com/ayoubachak/echolib |
| Summary | An AI-driven library for generating content using HuggingFace and LMStudio models. |
| upload_time | 2024-12-07 14:57:38 |
| maintainer | None |
| docs_url | None |
| author | Ayoub Achak |
| requires_python | >=3.8 |
| license | None |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Run
make sure to have the following 3 files :
- `hf_models.json`
```json
[
{
"id" : 1,
"name" : "Mistral v0.2 ( HuggingFace )",
"type" : "HUGGINGFACE",
"kwargs" : {
"api_url": "https://api-inference.huggingface.co/models",
"headers": {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
},
"model_huggingface_id": "mistralai/Mistral-7B-Instruct-v0.2",
"default_parameters": {
"max_length": -1,
"max_new_tokens": 250,
"temperature": 1e-8,
"use_cache": true,
"wait_for_model": true
}
},
"preset" : 1
},
{
"id" : 2,
"name" : "Mistral v0.3 ( HuggingFace )",
"type" : "HUGGINGFACE",
"kwargs" : {
"api_url": "https://api-inference.huggingface.co/models",
"headers": {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
},
"model_huggingface_id": "mistralai/Mistral-7B-Instruct-v0.3",
"default_parameters": {
"max_length": -1,
"max_new_tokens": 250,
"temperature": 1e-8,
"use_cache": true,
"wait_for_model": true
}
},
"preset" : 1
},
{
"id" : 3,
"name" : "Phi 3 mini ( HuggingFace )",
"type" : "HUGGINGFACE",
"kwargs" : {
"api_url": "https://api-inference.huggingface.co/models",
"headers": {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
},
"model_huggingface_id": "microsoft/Phi-3-mini-4k-instruct",
"default_parameters": {
"max_length": -1,
"max_new_tokens": 250,
"temperature": 1e-8,
"use_cache": true,
"wait_for_model": true
}
},
"preset" : 2
}
]
```
- `presets.json`
```json
[
{
"id" : 1,
"name" : "Mistral Instruct",
"input_prefix" : "[INST]",
"input_suffix" : "[/INST]",
"antiprompt" : "[INST]",
"pre_prompt" : "",
"pre_prompt_prefix" : "",
"pre_prompt_suffix" : ""
},
{
"id" : 2,
"name" : "Phi 3",
"input_prefix" : "<|user|>\n",
"input_suffix" : "<|end|>\n<|assistant|>\n",
"antiprompt" : "\"<|end|>\", \"<|assistant|>\"",
"pre_prompt" : "",
"pre_prompt_prefix" : "<|end|>\n",
"pre_prompt_suffix" : "<|system|>\n"
}
]
```
- `tokens.json` : More tokens mean more reliability and fault tolerence, in my case I used 10 HuggingFace tokens.
```json
[
{
"id": 1,
"name": "First",
"value": "A HuggingFace api token"
},
{
"id": 2,
"name": "Second",
"value": "Another token just to make sure the requests don't fail"
},
{
"id": 3,
"name": "Third",
"value": "a third token as a backup"
}
... Add more as needed
]
```
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"description": "# Run\n\nmake sure to have the following 3 files :\n- `hf_models.json` \n```json\n[\n {\n \"id\" : 1,\n \"name\" : \"Mistral v0.2 ( HuggingFace )\",\n \"type\" : \"HUGGINGFACE\",\n \"kwargs\" : {\n \"api_url\": \"https://api-inference.huggingface.co/models\",\n \"headers\": {\n \"Authorization\": \"Bearer YOUR_API_KEY\",\n \"Content-Type\": \"application/json\"\n },\n \"model_huggingface_id\": \"mistralai/Mistral-7B-Instruct-v0.2\",\n \"default_parameters\": {\n \"max_length\": -1,\n \"max_new_tokens\": 250,\n \"temperature\": 1e-8,\n \"use_cache\": true,\n \"wait_for_model\": true\n }\n },\n \"preset\" : 1\n },\n {\n \"id\" : 2,\n \"name\" : \"Mistral v0.3 ( HuggingFace )\",\n \"type\" : \"HUGGINGFACE\",\n \"kwargs\" : {\n \"api_url\": \"https://api-inference.huggingface.co/models\",\n \"headers\": {\n \"Authorization\": \"Bearer YOUR_API_KEY\",\n \"Content-Type\": \"application/json\"\n },\n \"model_huggingface_id\": \"mistralai/Mistral-7B-Instruct-v0.3\",\n \"default_parameters\": {\n \"max_length\": -1,\n \"max_new_tokens\": 250,\n \"temperature\": 1e-8,\n \"use_cache\": true,\n \"wait_for_model\": true\n }\n },\n \"preset\" : 1\n },\n {\n \"id\" : 3,\n \"name\" : \"Phi 3 mini ( HuggingFace )\",\n \"type\" : \"HUGGINGFACE\",\n \"kwargs\" : {\n \"api_url\": \"https://api-inference.huggingface.co/models\",\n \"headers\": {\n \"Authorization\": \"Bearer YOUR_API_KEY\",\n \"Content-Type\": \"application/json\"\n },\n \"model_huggingface_id\": \"microsoft/Phi-3-mini-4k-instruct\",\n \"default_parameters\": {\n \"max_length\": -1,\n \"max_new_tokens\": 250,\n \"temperature\": 1e-8,\n \"use_cache\": true,\n \"wait_for_model\": true\n }\n },\n \"preset\" : 2\n }\n]\n```\n- `presets.json`\n```json\n[\n {\n \"id\" : 1,\n \"name\" : \"Mistral Instruct\",\n \"input_prefix\" : \"[INST]\",\n \"input_suffix\" : \"[/INST]\",\n \"antiprompt\" : \"[INST]\",\n \"pre_prompt\" : \"\",\n \"pre_prompt_prefix\" : \"\",\n \"pre_prompt_suffix\" : \"\"\n },\n {\n \"id\" : 2,\n \"name\" : \"Phi 3\",\n \"input_prefix\" : \"<|user|>\\n\",\n \"input_suffix\" : \"<|end|>\\n<|assistant|>\\n\",\n \"antiprompt\" : \"\\\"<|end|>\\\", \\\"<|assistant|>\\\"\",\n \"pre_prompt\" : \"\",\n \"pre_prompt_prefix\" : \"<|end|>\\n\",\n \"pre_prompt_suffix\" : \"<|system|>\\n\"\n }\n]\n```\n- `tokens.json` : More tokens mean more reliability and fault tolerence, in my case I used 10 HuggingFace tokens.\n```json\n[\n {\n \"id\": 1,\n \"name\": \"First\",\n \"value\": \"A HuggingFace api token\"\n },\n {\n \"id\": 2,\n \"name\": \"Second\",\n \"value\": \"Another token just to make sure the requests don't fail\"\n },\n {\n \"id\": 3,\n \"name\": \"Third\",\n \"value\": \"a third token as a backup\"\n }\n ... Add more as needed\n]\n```\n\n",
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