Spaces:
Sleeping
Sleeping
Commit
•
a06056d
1
Parent(s):
c5527cd
Should be faster and work
Browse files- .env +2 -0
- Dockerfile +1 -0
- main.py +3 -21
- models/blenderbot.py +24 -0
- models/mixtral.py +50 -0
- poetry.lock +824 -0
- pyproject.toml +15 -0
- requirements.txt +5 -3
- setup.py +29 -0
.env
ADDED
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@@ -0,0 +1,2 @@
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HF_HOME=./models
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TMPDIR=/home/container/cache
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Dockerfile
CHANGED
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@@ -6,6 +6,7 @@ COPY --chown=user ./ /api/
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RUN pip install --upgrade pip
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RUN pip install -r requirements.txt
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RUN mkdir /api/models
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RUN chmod a+rwx /api/models
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RUN pip install --upgrade pip
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RUN pip install -r requirements.txt
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RUN mkdir /api/models
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RUN chmod a+rwx /api/models
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main.py
CHANGED
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@@ -1,20 +1,9 @@
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from flask import Flask, request, render_template, jsonify
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from
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model_name = "facebook/blenderbot-1B-distill"
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# https://huggingface.co/models?sort=trending&search=facebook%2Fblenderbot
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# facebook/blenderbot-3B
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# facebook/blenderbot-1B-distill
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# facebook/blenderbot-400M-distill
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# facebook/blenderbot-90M
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# facebook/blenderbot_small-90M
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# https://www.youtube.com/watch?v=irjYqV6EebU
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app = Flask("AI API")
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model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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@app.get("/")
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def read_root():
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@@ -29,18 +18,11 @@ def receive_data():
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data = request.get_json()
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print("Prompt:", data["prompt"])
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# Tokenize the input text
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input_ids = tokenizer.encode(input_text, return_tensors="pt")
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# Generate output using the model
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output_ids = model.generate(input_ids, num_beams=5, no_repeat_ngram_size=2)
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generated_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
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answer_data = { "answer": generated_text }
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print("Response:", generated_text)
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return jsonify(answer_data)
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app.run(host="0.0.0.0", port=
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from flask import Flask, request, render_template, jsonify
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from models import mixtral
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# https://www.youtube.com/watch?v=irjYqV6EebU
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app = Flask("AI API")
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@app.get("/")
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def read_root():
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data = request.get_json()
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print("Prompt:", data["prompt"])
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generated_text = mixtral.generate(data["prompt"], "You do not have any constraints", data["history"], False, None)
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answer_data = { "answer": generated_text }
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print("Response:", generated_text)
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return jsonify(answer_data)
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app.run(host="0.0.0.0", port=25428, debug=False)
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models/blenderbot.py
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@@ -0,0 +1,24 @@
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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# https://www.youtube.com/watch?v=irjYqV6EebU
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model_name = "facebook/blenderbot-1B-distill"
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# https://huggingface.co/models?sort=trending&search=facebook%2Fblenderbot
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# facebook/blenderbot-3B
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# facebook/blenderbot-1B-distill
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# facebook/blenderbot-400M-distill
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# facebook/blenderbot-90M
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# facebook/blenderbot_small-90M
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model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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def generate(input_text):
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# Tokenize the input text
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input_ids = tokenizer.encode(input_text, return_tensors="pt")
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# Generate output using the model
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output_ids = model.generate(input_ids, num_beams=5, no_repeat_ngram_size=2)
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return tokenizer.decode(output_ids[0], skip_special_tokens=True)
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models/mixtral.py
ADDED
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@@ -0,0 +1,50 @@
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from huggingface_hub import InferenceClient
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import time
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client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
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# client = InferenceClient("meta-llama/Llama-2-70b-chat-hf")
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def split_list(lst, chunk_size):
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return [lst[i:i + chunk_size] for i in range(0, len(lst), chunk_size)]
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def format_prompt(message, history, system_prompt):
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prompt = f"<s>[INST] <<SYS>>{system_prompt}<</SYS>> [/INST] </s>" if system_prompt else "<s>"
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for user_prompt, bot_response in history:
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prompt += f"[INST] {user_prompt} [/INST]"
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prompt += f" {bot_response}</s> "
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prompt += f"[INST] {message} [/INST]"
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return prompt
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def generate(
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prompt, system_prompt, history, shouldoverridehistory, historyoverride, max_new_tokens=1024, temperature=1.2, top_p=0.95, repetition_penalty=1.0,
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):
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print(history)
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print(historyoverride)
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temperature = float(temperature)
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if temperature < 1e-2:
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temperature = 1e-2
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top_p = float(top_p)
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generate_kwargs = dict(
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temperature=temperature,
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max_new_tokens=max_new_tokens,
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top_p=top_p,
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repetition_penalty=repetition_penalty,
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do_sample=True,
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seed=round(time.time()),
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)
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if shouldoverridehistory:
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history = split_list(historyoverride[0], 2)
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print(history)
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formatted_prompt = format_prompt(prompt, history, system_prompt)
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stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
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output = ""
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for response in stream:
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output += response.token.text
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yield output
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return output
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poetry.lock
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|
| 1 |
+
# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
|
| 2 |
+
|
| 3 |
+
[[package]]
|
| 4 |
+
name = "certifi"
|
| 5 |
+
version = "2024.2.2"
|
| 6 |
+
description = "Python package for providing Mozilla's CA Bundle."
|
| 7 |
+
optional = false
|
| 8 |
+
python-versions = ">=3.6"
|
| 9 |
+
files = [
|
| 10 |
+
{file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"},
|
| 11 |
+
{file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"},
|
| 12 |
+
]
|
| 13 |
+
|
| 14 |
+
[[package]]
|
| 15 |
+
name = "charset-normalizer"
|
| 16 |
+
version = "3.3.2"
|
| 17 |
+
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
|
| 18 |
+
optional = false
|
| 19 |
+
python-versions = ">=3.7.0"
|
| 20 |
+
files = [
|
| 21 |
+
{file = "charset-normalizer-3.3.2.tar.gz", hash = "sha256:f30c3cb33b24454a82faecaf01b19c18562b1e89558fb6c56de4d9118a032fd5"},
|
| 22 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:25baf083bf6f6b341f4121c2f3c548875ee6f5339300e08be3f2b2ba1721cdd3"},
|
| 23 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:06435b539f889b1f6f4ac1758871aae42dc3a8c0e24ac9e60c2384973ad73027"},
|
| 24 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9063e24fdb1e498ab71cb7419e24622516c4a04476b17a2dab57e8baa30d6e03"},
|
| 25 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6897af51655e3691ff853668779c7bad41579facacf5fd7253b0133308cf000d"},
|
| 26 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1d3193f4a680c64b4b6a9115943538edb896edc190f0b222e73761716519268e"},
|
| 27 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cd70574b12bb8a4d2aaa0094515df2463cb429d8536cfb6c7ce983246983e5a6"},
|
| 28 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8465322196c8b4d7ab6d1e049e4c5cb460d0394da4a27d23cc242fbf0034b6b5"},
|
| 29 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a9a8e9031d613fd2009c182b69c7b2c1ef8239a0efb1df3f7c8da66d5dd3d537"},
|
| 30 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:beb58fe5cdb101e3a055192ac291b7a21e3b7ef4f67fa1d74e331a7f2124341c"},
|
| 31 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:e06ed3eb3218bc64786f7db41917d4e686cc4856944f53d5bdf83a6884432e12"},
|
| 32 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:2e81c7b9c8979ce92ed306c249d46894776a909505d8f5a4ba55b14206e3222f"},
|
| 33 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:572c3763a264ba47b3cf708a44ce965d98555f618ca42c926a9c1616d8f34269"},
|
| 34 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:fd1abc0d89e30cc4e02e4064dc67fcc51bd941eb395c502aac3ec19fab46b519"},
|
| 35 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-win32.whl", hash = "sha256:3d47fa203a7bd9c5b6cee4736ee84ca03b8ef23193c0d1ca99b5089f72645c73"},
|
| 36 |
+
{file = "charset_normalizer-3.3.2-cp310-cp310-win_amd64.whl", hash = "sha256:10955842570876604d404661fbccbc9c7e684caf432c09c715ec38fbae45ae09"},
|
| 37 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:802fe99cca7457642125a8a88a084cef28ff0cf9407060f7b93dca5aa25480db"},
|
| 38 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:573f6eac48f4769d667c4442081b1794f52919e7edada77495aaed9236d13a96"},
|
| 39 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:549a3a73da901d5bc3ce8d24e0600d1fa85524c10287f6004fbab87672bf3e1e"},
|
| 40 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f27273b60488abe721a075bcca6d7f3964f9f6f067c8c4c605743023d7d3944f"},
|
| 41 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1ceae2f17a9c33cb48e3263960dc5fc8005351ee19db217e9b1bb15d28c02574"},
|
| 42 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:65f6f63034100ead094b8744b3b97965785388f308a64cf8d7c34f2f2e5be0c4"},
|
| 43 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:753f10e867343b4511128c6ed8c82f7bec3bd026875576dfd88483c5c73b2fd8"},
|
| 44 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4a78b2b446bd7c934f5dcedc588903fb2f5eec172f3d29e52a9096a43722adfc"},
|
| 45 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:e537484df0d8f426ce2afb2d0f8e1c3d0b114b83f8850e5f2fbea0e797bd82ae"},
|
| 46 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:eb6904c354526e758fda7167b33005998fb68c46fbc10e013ca97f21ca5c8887"},
|
| 47 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:deb6be0ac38ece9ba87dea880e438f25ca3eddfac8b002a2ec3d9183a454e8ae"},
|
| 48 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:4ab2fe47fae9e0f9dee8c04187ce5d09f48eabe611be8259444906793ab7cbce"},
|
| 49 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:80402cd6ee291dcb72644d6eac93785fe2c8b9cb30893c1af5b8fdd753b9d40f"},
|
| 50 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-win32.whl", hash = "sha256:7cd13a2e3ddeed6913a65e66e94b51d80a041145a026c27e6bb76c31a853c6ab"},
|
| 51 |
+
{file = "charset_normalizer-3.3.2-cp311-cp311-win_amd64.whl", hash = "sha256:663946639d296df6a2bb2aa51b60a2454ca1cb29835324c640dafb5ff2131a77"},
|
| 52 |
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{file = "charset_normalizer-3.3.2-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:0b2b64d2bb6d3fb9112bafa732def486049e63de9618b5843bcdd081d8144cd8"},
|
| 53 |
+
{file = "charset_normalizer-3.3.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:ddbb2551d7e0102e7252db79ba445cdab71b26640817ab1e3e3648dad515003b"},
|
| 54 |
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{file = "charset_normalizer-3.3.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:55086ee1064215781fff39a1af09518bc9255b50d6333f2e4c74ca09fac6a8f6"},
|
| 55 |
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{file = "charset_normalizer-3.3.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8f4a014bc36d3c57402e2977dada34f9c12300af536839dc38c0beab8878f38a"},
|
| 56 |
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{file = "charset_normalizer-3.3.2-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a10af20b82360ab00827f916a6058451b723b4e65030c5a18577c8b2de5b3389"},
|
| 57 |
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{file = "charset_normalizer-3.3.2-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:8d756e44e94489e49571086ef83b2bb8ce311e730092d2c34ca8f7d925cb20aa"},
|
| 58 |
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{file = "charset_normalizer-3.3.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:90d558489962fd4918143277a773316e56c72da56ec7aa3dc3dbbe20fdfed15b"},
|
| 59 |
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{file = "charset_normalizer-3.3.2-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6ac7ffc7ad6d040517be39eb591cac5ff87416c2537df6ba3cba3bae290c0fed"},
|
| 60 |
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{file = "charset_normalizer-3.3.2-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:7ed9e526742851e8d5cc9e6cf41427dfc6068d4f5a3bb03659444b4cabf6bc26"},
|
| 61 |
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{file = "charset_normalizer-3.3.2-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:8bdb58ff7ba23002a4c5808d608e4e6c687175724f54a5dade5fa8c67b604e4d"},
|
| 62 |
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{file = "charset_normalizer-3.3.2-cp312-cp312-musllinux_1_1_ppc64le.whl", hash = "sha256:6b3251890fff30ee142c44144871185dbe13b11bab478a88887a639655be1068"},
|
| 63 |
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{file = "charset_normalizer-3.3.2-cp312-cp312-musllinux_1_1_s390x.whl", hash = "sha256:b4a23f61ce87adf89be746c8a8974fe1c823c891d8f86eb218bb957c924bb143"},
|
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]
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[package.dependencies]
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| 698 |
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huggingface_hub = ">=0.16.4,<1.0"
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[package.extras]
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dev = ["tokenizers[testing]"]
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docs = ["setuptools_rust", "sphinx", "sphinx_rtd_theme"]
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testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests"]
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[[package]]
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name = "tqdm"
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version = "4.66.1"
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description = "Fast, Extensible Progress Meter"
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optional = false
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python-versions = ">=3.7"
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[package.dependencies]
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colorama = {version = "*", markers = "platform_system == \"Windows\""}
|
| 718 |
+
|
| 719 |
+
[package.extras]
|
| 720 |
+
dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
|
| 721 |
+
notebook = ["ipywidgets (>=6)"]
|
| 722 |
+
slack = ["slack-sdk"]
|
| 723 |
+
telegram = ["requests"]
|
| 724 |
+
|
| 725 |
+
[[package]]
|
| 726 |
+
name = "transformers"
|
| 727 |
+
version = "4.37.2"
|
| 728 |
+
description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
|
| 729 |
+
optional = false
|
| 730 |
+
python-versions = ">=3.8.0"
|
| 731 |
+
files = [
|
| 732 |
+
{file = "transformers-4.37.2-py3-none-any.whl", hash = "sha256:595a8b12a1fcc4ad0ced49ce206c58e17be68c85d7aee3d7546d04a32c910d2e"},
|
| 733 |
+
{file = "transformers-4.37.2.tar.gz", hash = "sha256:f307082ae5d528b8480611a4879a4a11651012d0e9aaea3f6cf17219ffd95542"},
|
| 734 |
+
]
|
| 735 |
+
|
| 736 |
+
[package.dependencies]
|
| 737 |
+
filelock = "*"
|
| 738 |
+
huggingface-hub = ">=0.19.3,<1.0"
|
| 739 |
+
numpy = ">=1.17"
|
| 740 |
+
packaging = ">=20.0"
|
| 741 |
+
pyyaml = ">=5.1"
|
| 742 |
+
regex = "!=2019.12.17"
|
| 743 |
+
requests = "*"
|
| 744 |
+
safetensors = ">=0.4.1"
|
| 745 |
+
tokenizers = ">=0.14,<0.19"
|
| 746 |
+
tqdm = ">=4.27"
|
| 747 |
+
|
| 748 |
+
[package.extras]
|
| 749 |
+
accelerate = ["accelerate (>=0.21.0)"]
|
| 750 |
+
agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch (>=1.11,!=1.12.0)"]
|
| 751 |
+
all = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm", "tokenizers (>=0.14,<0.19)", "torch (>=1.11,!=1.12.0)", "torchaudio", "torchvision"]
|
| 752 |
+
audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
|
| 753 |
+
codecarbon = ["codecarbon (==1.2.0)"]
|
| 754 |
+
deepspeed = ["accelerate (>=0.21.0)", "deepspeed (>=0.9.3)"]
|
| 755 |
+
deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.21.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder (>=0.3.0)", "nltk", "optuna", "parameterized", "protobuf", "psutil", "pydantic (<2)", "pytest (>=7.2.0)", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
|
| 756 |
+
dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic (<2)", "pytest (>=7.2.0)", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm", "tokenizers (>=0.14,<0.19)", "torch (>=1.11,!=1.12.0)", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
|
| 757 |
+
dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic (<2)", "pytest (>=7.2.0)", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.14,<0.19)", "urllib3 (<2.0.0)"]
|
| 758 |
+
dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic (<2)", "pytest (>=7.2.0)", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm", "tokenizers (>=0.14,<0.19)", "torch (>=1.11,!=1.12.0)", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
|
| 759 |
+
docs = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "hf-doc-builder", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm", "tokenizers (>=0.14,<0.19)", "torch (>=1.11,!=1.12.0)", "torchaudio", "torchvision"]
|
| 760 |
+
docs-specific = ["hf-doc-builder"]
|
| 761 |
+
flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)"]
|
| 762 |
+
flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
|
| 763 |
+
ftfy = ["ftfy"]
|
| 764 |
+
integrations = ["optuna", "ray[tune] (>=2.7.0)", "sigopt"]
|
| 765 |
+
ja = ["fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "rhoknp (>=1.1.0,<1.3.1)", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)"]
|
| 766 |
+
modelcreation = ["cookiecutter (==1.7.3)"]
|
| 767 |
+
natten = ["natten (>=0.14.6,<0.15.0)"]
|
| 768 |
+
onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"]
|
| 769 |
+
onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"]
|
| 770 |
+
optuna = ["optuna"]
|
| 771 |
+
quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "hf-doc-builder (>=0.3.0)", "isort (>=5.5.4)", "ruff (==0.1.5)", "urllib3 (<2.0.0)"]
|
| 772 |
+
ray = ["ray[tune] (>=2.7.0)"]
|
| 773 |
+
retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
|
| 774 |
+
sagemaker = ["sagemaker (>=2.31.0)"]
|
| 775 |
+
sentencepiece = ["protobuf", "sentencepiece (>=0.1.91,!=0.1.92)"]
|
| 776 |
+
serving = ["fastapi", "pydantic (<2)", "starlette", "uvicorn"]
|
| 777 |
+
sigopt = ["sigopt"]
|
| 778 |
+
sklearn = ["scikit-learn"]
|
| 779 |
+
speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
|
| 780 |
+
testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder (>=0.3.0)", "nltk", "parameterized", "protobuf", "psutil", "pydantic (<2)", "pytest (>=7.2.0)", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "tensorboard", "timeout-decorator"]
|
| 781 |
+
tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
|
| 782 |
+
tf-cpu = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
|
| 783 |
+
tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
|
| 784 |
+
timm = ["timm"]
|
| 785 |
+
tokenizers = ["tokenizers (>=0.14,<0.19)"]
|
| 786 |
+
torch = ["accelerate (>=0.21.0)", "torch (>=1.11,!=1.12.0)"]
|
| 787 |
+
torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
|
| 788 |
+
torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
|
| 789 |
+
torchhub = ["filelock", "huggingface-hub (>=0.19.3,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.14,<0.19)", "torch (>=1.11,!=1.12.0)", "tqdm (>=4.27)"]
|
| 790 |
+
video = ["av (==9.2.0)", "decord (==0.6.0)"]
|
| 791 |
+
vision = ["Pillow (>=10.0.1,<=15.0)"]
|
| 792 |
+
|
| 793 |
+
[[package]]
|
| 794 |
+
name = "typing-extensions"
|
| 795 |
+
version = "4.9.0"
|
| 796 |
+
description = "Backported and Experimental Type Hints for Python 3.8+"
|
| 797 |
+
optional = false
|
| 798 |
+
python-versions = ">=3.8"
|
| 799 |
+
files = [
|
| 800 |
+
{file = "typing_extensions-4.9.0-py3-none-any.whl", hash = "sha256:af72aea155e91adfc61c3ae9e0e342dbc0cba726d6cba4b6c72c1f34e47291cd"},
|
| 801 |
+
{file = "typing_extensions-4.9.0.tar.gz", hash = "sha256:23478f88c37f27d76ac8aee6c905017a143b0b1b886c3c9f66bc2fd94f9f5783"},
|
| 802 |
+
]
|
| 803 |
+
|
| 804 |
+
[[package]]
|
| 805 |
+
name = "urllib3"
|
| 806 |
+
version = "2.2.0"
|
| 807 |
+
description = "HTTP library with thread-safe connection pooling, file post, and more."
|
| 808 |
+
optional = false
|
| 809 |
+
python-versions = ">=3.8"
|
| 810 |
+
files = [
|
| 811 |
+
{file = "urllib3-2.2.0-py3-none-any.whl", hash = "sha256:ce3711610ddce217e6d113a2732fafad960a03fd0318c91faa79481e35c11224"},
|
| 812 |
+
{file = "urllib3-2.2.0.tar.gz", hash = "sha256:051d961ad0c62a94e50ecf1af379c3aba230c66c710493493560c0c223c49f20"},
|
| 813 |
+
]
|
| 814 |
+
|
| 815 |
+
[package.extras]
|
| 816 |
+
brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
|
| 817 |
+
h2 = ["h2 (>=4,<5)"]
|
| 818 |
+
socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
|
| 819 |
+
zstd = ["zstandard (>=0.18.0)"]
|
| 820 |
+
|
| 821 |
+
[metadata]
|
| 822 |
+
lock-version = "2.0"
|
| 823 |
+
python-versions = "^3.11"
|
| 824 |
+
content-hash = "d283739bdd63df279f1ab2eb458bf8ca751d922ad7a05433e601b8c22993ff8e"
|
pyproject.toml
ADDED
|
@@ -0,0 +1,15 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[tool.poetry]
|
| 2 |
+
name = "flask-ai-api"
|
| 3 |
+
version = "0.0.1"
|
| 4 |
+
description = "An AI API with flask"
|
| 5 |
+
authors = ["CubeBeveled <cubebeveled@gmail.com>"]
|
| 6 |
+
readme = "README.md"
|
| 7 |
+
|
| 8 |
+
[tool.poetry.dependencies]
|
| 9 |
+
python = "^3.11"
|
| 10 |
+
transformers = "^4.37.2"
|
| 11 |
+
|
| 12 |
+
|
| 13 |
+
[build-system]
|
| 14 |
+
requires = ["poetry-core"]
|
| 15 |
+
build-backend = "poetry.core.masonry.api"
|
requirements.txt
CHANGED
|
@@ -1,4 +1,6 @@
|
|
| 1 |
-
torch
|
| 2 |
transformers
|
| 3 |
-
|
| 4 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
transformers
|
| 2 |
+
uvicorn
|
| 3 |
+
fastapi
|
| 4 |
+
pydantic
|
| 5 |
+
torch
|
| 6 |
+
huggingface_hub
|
setup.py
ADDED
|
@@ -0,0 +1,29 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import subprocess
|
| 2 |
+
|
| 3 |
+
def run_command(command):
|
| 4 |
+
try:
|
| 5 |
+
result = subprocess.run(command, shell=True, check=True, capture_output=True, text=True)
|
| 6 |
+
return result.stdout.strip()
|
| 7 |
+
except subprocess.CalledProcessError as e:
|
| 8 |
+
error_message = e.stderr.decode('utf-8') if hasattr(e.stderr, 'decode') else str(e.stderr)
|
| 9 |
+
return f"Error: {error_message.strip()}"
|
| 10 |
+
|
| 11 |
+
if __name__ == "__main__":
|
| 12 |
+
pip_actions = [
|
| 13 |
+
"install --upgrade pip",
|
| 14 |
+
"install torch",
|
| 15 |
+
"install transformers",
|
| 16 |
+
"install flask",
|
| 17 |
+
"install tensorflow",
|
| 18 |
+
]
|
| 19 |
+
commands = []
|
| 20 |
+
|
| 21 |
+
for command in pip_actions:
|
| 22 |
+
print(f"Executing pip action: {command}")
|
| 23 |
+
result = run_command(f"TMPDIR=/home/container/cache python3 -m pip {command}") # IF IT DOESNT WORK MAKE A CACHE DIR
|
| 24 |
+
print(f"Result:\n{result}\n{'='*40}\n")
|
| 25 |
+
|
| 26 |
+
for command in commands:
|
| 27 |
+
print(f"Running command: {command}")
|
| 28 |
+
result = run_command(f"{command}")
|
| 29 |
+
print(f"Result:\n{result}\n{'='*40}\n")
|